Intelligent system for generating and executing a sheet metal bending plan

ABSTRACT

An intelligent sheet metal bending system is disclosed, having a cooperative generative planning system. A planning module interacts with several expert modules to develop a bending plan. The planning module utilizes a state-space search algorithm. Computerized methods are provided for selecting a robot gripper and a repo gripper, and for determining the optimal placement of such grippers as they are holding a workpiece being formed by the bending apparatus. Computerized methods are provided for selecting tooling to be used by the bending apparatus, and for determining a tooling stage layout. An operations planning method is provided which allows the bending apparatus to be set up concurrently while time-consuming calculations, such as motion planning, are performed. An additional method or system is provided for positioning tooling stages by using a backstage guide member which guides placement of a tooling stage along the die rail of the bending apparatus. A method is provided for learning motion control offset values, and for eliminating the need for superfluous sensor-based control operations once the motion control offset values are known. The planning system may be used for facilitating functions such as design and assembly system, which may perform designing, costing, scheduling, and/or manufacture and assembly.

RELATED APPLICATION DATA

This is a divisional application of U.S. application Ser. No. 09/207,268filed Dec. 8, 1998, (now U.S. Pat. No. 6,341,243, issued Jan. 22, 2002),which is a continuation of U.S. patent application No. 08/386,369, filedFeb. 9, 1995 (now U.S. Pat. No. 5,969,973, issued on Oct. 19, 1999),which is a continuation of U.S. application Ser. No. 08/338,113, filedNov. 9, 1994, now abandoned, the contents of the above applicationsbeing expressly incorporated by reference in their entireties. Thepresent disclosure is also related to the disclosures provided in thefollowing U.S. applications filed on Dec. 8, 1998: “Method forPlanning/Controlling Robot Motion”, U.S. patent application Ser. No.08/338,115, filed on Nov. 9, 1994; “Methods for Backgaging andSensor-Based Control of Bending Operations”, U.S. patent applicationSer. No. 08/338,153, filed on Nov. 9, 1994; and “Fingerpad Force SensingSystem”, U.S. patent application Ser. No. 08/338,095, filed on Nov. 9,1994; and the disclosures of all of these applications are expresslyincorporated by reference herein in their entireties.

MICROFICHE APPENDIX

This application includes a microfiche appendix for appendices A-D. Themicrofiche appendix consists of one fiche including 32 frames.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patentdisclosure, as it appears in the Patent and Trademark Office patentfiles or records, but otherwise reserves all copyright rightswhatsoever.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is directed to methods and subsystems which may beprovided in an intelligent bent sheet metal designing, planning andmanufacturing system and the like.

2. Discussion of Background Information

FIGS. 1-3 illustrate, in a simplified view, an example conventionalbending workstation 10 for bending a sheet metal part (workpiece) 16under the control of a manually created program downloaded to variouscontrol devices provided within the workstation. The illustrated bendingworkstation 10 is a BM100 Amada workstation.

(a) The Hardware and Its Operation

FIG. 1 shows an overall simplified view of bending workstation 10. FIG.2 shows a partial view of a press brake 29, positioned to perform a bendan a workpiece 16. The elements shown in FIG. 2 include a robot arm 12having a robot arm gripper 14 grasping a workpiece 16, a punch 13 beingheld by a punch holder 20, and a die 19 which is placed on a die rail22. A backgage mechanism 24 is illustrated to the left of punch 18 anddie 19.

As shown in FIG. 1, bending workstation 10 includes four significantmechanical components: a press brake 29 for bending workpiece 16; a fivedegree-of-freedom (5 DOF) robotic manipulator (robot) 12 for handlingand positioning workpiece 16 within press brake 29; a materialloader/unloader (L/UL) 30 for loading and positioning a blank workpieceat a location for robot 12 to grab, and for unloading finishedworkpieces; and a repositioning gripper 32 for holding workpiece 16while robot 12 changes its grasp.

Press brake 29 includes several components as illustrated in FIGS. 1-3.Viewing FIG. 3, press brake 29 includes at least one die 19 which isplaced on a die rail 22, and at least one corresponding punch tool 18which is held by a punch tool holder 20. Press brake 29 further includesa backgage mechanism 24.

As shown in FIG. 2, robot arm 12 includes a robot arm gripper 14 whichis used to grasp workpiece 16. As shown in FIG. 1, materialloader/unloader 30 includes several suction cups 31 which create anupwardly directed suction force for lifting a sheet metal workpiece 16,thereby allowing L/UL 30 to pass workpiece 16 to gripper 14 of robot 12,and to subsequently retrieve a finished workpiece 16 from gripper 14 andunload the finished workpiece.

In operation, loader/unloader (L/UL) 30 will lift a blank workpiece 16from a receptacle (not shown), and will raise and move workpiece 16 to aposition to be grabbed by gripper 14 of robot 12. Robot 12 thenmaneuvers itself to a position corresponding to a particular bendingstage located within bending workstation 10. Referring to each of FIGS.1 and 3, stage 1 comprises the stage at the leftmost portion of pressbrake 29, and stage 2 is located to the right of stage 1 along die rail22.

If the first bend is to be made at stage 1, robot 12 will move workpiece16 to stage 1, and as shown in FIG. 2, will maneuver workpiece 16 withinpress brake 29, at a location between punch tool 11 and die 19, until itreaches and touches a backstop portion of backgage mechanism 24. Withthe aid of backgage mechanism 24, the position of workpiece 16 isadjusted by robot arm 12. Then, a bend operation is performed onworkpiece 16 at stage 1. In performing the bend operation, die rail 22moves upward (along a D axis), as indicated by the directional arrow Ain FIG. 2. As punch tool 18 and die 19 simultaneously contact workpiece16, so that workpiece 16 assumes a relatively stable position withinpress brake 29, gripper 14 will release its grasp on workpiece 16, androbot 12 will move gripper 14 away from workpiece 16. Press brake 29will then complete its bending of workpiece 16, by completing the upwardmovement of die 19 until the proper bend has been formed.

Once die 19 is engaged against punch tool 18, holding workpiece 16 inits bent state, before disengaging die 19 by lowering press brake 29,robot arm 12 will reposition its robot arm gripper 14 to hold workpiece16. Once gripper 14 is holding workpiece 16, die 19 will be disengagedby releasing press brake 29. Robot 12 then maneuvers and repositionsworkpiece 16 in order to perform the next bend in the particular bendsequence that has been programmed for workpiece 16. The next bend withinthe bend sequence may be performed either at the same stage, or at adifferent stage, such as stage 2, depending upon the type of bends to beperformed, and the tooling prided within press brake 29.

Depending upon the next bend to be performed, and the configuration ofworkpiece 16, the gripping position of gripper 14 may need to berepositioned. Repositioning gripper 32, shown in FIG. 1, is provided forthis purpose. Before performing the next bend, for which repositioningof robot gripper 14 is needed, workpiece 16 will be moved by robot 12 torepositioning gripper 32. Repositioning gripper 32 will then graspworkpiece 16 so that robot gripper 14 can regrip workpiece 16 at alocation appropriate for the next bend or sequence of bends.

(b) The Control System

The bending workstation 10 illustrated in FIG. 1 is controlled byseveral control devices which are housed separately, including anMM20-CAPS interface 40, a press brake controller 42, a robot controller44, and a load/unload unit controller 46. Press brake controller 42comprises an NC9R press brake controller, and robot controller 44comprises a 25B robot controller, which are each supplied by Amada. Eachof press brake controller 42 and robot controller 44 have their own CPUand programming environments. Load/unload unit controller 46 comprises astand alone Programmable Logic Controller (PLC), and is wired torespective consoles provided for press brake controller 42 and robotcontroller 44.

Each of controllers 42, 44, and 46 has a different style bus,architecture, and manufacturer. They are coordinated primarily byparallel I/O signals. Serial interfaces are provided for transportingbending and robot programs to the controllers, each of which isprogrammed in a different manner. For example, logic diagrams are usedto program the PLC of the load/unload controller 46, and RML is used toprogram robot controller 44.

(c) The Design/Manufacture Process

The overall design/manufacture process for bending sheet metal includesseveral steps. First, a part to be produced is typically designed usingan appropriate CAD system. Then, a plan is generated which defines thetooling to be used and a sequence of bends to be performed. Once theneeded tooling is determined, an operator will begin to set up thebending workstation. After the workstation is set up, the plan isexecuted, i.e., a workpiece is loaded and operation of the bendingworkstation is controlled to execute the complete sequence of bends on ablank sheet metal workpiece. The results of the initial runs of thebending workstation are then fed back to the design step, whereappropriate modifications may be made in the design of the part in viewof the actual operation of the system.

In the planning step, a plan is developed for bending workstation 10 inorder to configure the system to perform a sequence of bendingoperations. Needed hardware must be selected, including appropriatedies, punch tools, grippers, and so on. In addition, the bendingsequence must be determined, which includes the ordering and selectionof bends to be performed by bending workstation 10. In selecting thehardware, and in determining the bending sequence, along with otherparameters, software will be generated to operate bending workstation10, so that bending workstation 10 can automatically perform variousoperations of the bending process.

A plan for a BM100 bending workstation includes generated software suchas an NC9R press brake program and a 25B RML robot program. Each ofthese programs may be created with the use of an initial part designcreated from a CAD system. Both the robot program and the bendingprogram must be developed manually, and are quite labor-intensive.Previously developed programs are classified by the number of bendsand/or by the directions of the bends. Engineers examine each part styleto determine if previously developed and classified program may be usedor whether a new program must be written. However, since each classifiedprogram typically supports only a narrow range of acceptable partdimensions, new programs must frequently be written by the engineers.The final RML robot program, when complete, is compiled and downloadedby the MM20-CAPS system 40 to robot controller 44. The bending programis entered and debugged on a control pendant provided on press brakecontroller 42. After entering the robot and bending programs into thesystem, an operator performs several manual operations to walk thesystem through the several operations to be performed. For example, anoperator will manually operate a hand-held pendant of the robotcontroller to manually move the robot to the loading and unloadingpositions, after which the interface console 40 will store theappropriate locations into the final RML program to be compiled anddownloaded to robot controller 44. In addition, in producing the bendingprogram, the operator may control the system to follow the planned bendsequence, in order to determine the values for the backgage position (Laxis) and the die rail position (D axis).

(d) Intelligent Manufacturing Workstations

Various proposals have been made in order to overcome many of thedrawbacks with prior systems such as the BM100 Amada bendingworkstation, and research has been conducted in the area of intelligentmanufacturing workstations. Some proposed features of intelligent sheetmetal bending workstations included features such as open architecture,including open system configurations and distributed decision making,and enhanced computer aided design and geometric modeling systems.

A paper entitled “Intelligent Manufacturing Workstations” was presentedat the 1992 ASME Winter Annual Meeting regarding Knowledge-BasedAutomation of Processes on Nov. 13, 1992, by David Alan Bourne; thecontent of the Paper is expressly incorporated herein by reference in itentirety. In the Paper, an intelligent manufacturing workstation isdefined as a self-contained system that takes a new design for a partand manufactures it automatically. The process is stated to includeautomated setup, part programming, control, and feedback to design.

The Paper discusses several components of an coverall intelligentmanufacturing workstation, including features such as open architecturethe use of software modules that communicate via a query-based language,part design, operations planning, workstation control, and geometricmodeling.

(1) Open Architecture

It has been recognized that an effective intelligent manufacturingworkstation should have open software, open controller and openmechanism architecture. That is, a machine tool user operating such aworkstation should be able to add onto the software, the controller, andthe mechanism architectures of the workstation in order to improve theirfunctions.

(2) Software Modules Using Query-Based Language

Software modules have been suggested, in the above-noted paper by DavidBourne, for use in an intelligent manufacturing workstation. Suchmodules would be split along knowledge boundaries which have beendefined in industrial practice, including, e.g., tooling, operations,programming, planning and design. The software modules would beresponsible for understanding commands and data specifications, and foranswering questions in their own area of specialty. A particular modulemight be configured to request information from other modules so that ithas adequate information to solve its designated problems, tocommunicate in a standard language, and to work on several problems atonce. In addition, each module would know which other module to ask forinformation and provide assistance in formulating a question for thereceiving module. The general software architecture proposed in theabove-noted Paper is illustrated in FIG. 4. The proposed architectureincludes a designer 50, a bend sequence planner 52, a module 54 forsequence planning, execution and error handling, a modeler 56, a module58 for sensor interpretation, and modules 60, 62 for process control andholding, and fixturing. Each of the modules for sensor interpretation58, process control 60, and holding and fixturing 62 are coupled toexternal machine and sensor drives 64. A control subsystem 68 is formedby several of the modules, including sequence planning, execution anderror handling module 54, modeler 56, and the modules for sensorinterpretation 58, process control 60 and holding and fixturing 62.Control subsystem 68 is shown as being implemented within a Chimeraoperating system. All of the modules may be connected to other factorysystems 66, including, e.g., systems for scheduling, operations, andprocess planning.

(3) Design Tools

Experimentation has been conducted with design tools that constantlymanage the relationship between a stock part and a final part as it isapplied to sheet metal bending, as noted in the above-referenced Paper,and as disclosed by C. Wang in “A Parallel Designer for Sheet MetalParts,” Mechanical Engineering Master's Report, Carnegie Mellon (1992),the content of which is expressly incorporated herein by reference inits entirety. The design information, which may be described in 3D, oras a 2D flat pattern, is automatically maintained (in parallel) withanother representation of the developing part. In this way, a connectionbetween each of the features of the initial stock part and the finalpart is maintained.

(4) The Planning System

Once the design is complete, a planner typically then produces a planwhich will later be used to execute the manufacturing process. The planincludes several instructions regarding the sequencing of machineoperations to produce the desired part. An optimal plan will result in areduction of setup time, a reduction in the existence of scrap afterproduction of the parts, an increase in par quality, and an increase inproduction rate. To promulgate such advantages, the above-noted Paperrecommends that as much specific knowledge as possible be separated fromthe planner so that the planner can be easily adapted to differentmachines and processes. A “query-based” planning system is thus proposedwhich shifts the emphasis of the planner to asking expert questions,rather than attempting to act as a self-contained expert.

(5) Workstation Control

The above-noted Paper proposes that the controller use an off-the-shelfengineering UNIX workstation as the core computing resource. Theworkstation may include in its back-plane an extension rack ofspecial-purpose boards and an additional CPU that runs with a real-timeversion of the UNIX operating system, called CHIMERA-II. See, e.g.,STEWART et al., Robotics Institute Technical Report, entitled “CHIMERAII: A Real-Time UNIX-Compatible Multiprocessor operating System forSensor Based Control Applications,” Carnegie Mellon, CMU-RI-TR-89-24(1989), the content of which is expressly incorporated by referenceherein in its entirety.

(6) Geometric Modeling

Geometric modeling is an important component in intelligent machiningworkstations. Several modelers have been experimented with during aproject in the Robotics Institute at Carnegie Mellon University. Ageometric modeler called “NOODLES” has been proposed for use as amodeler in an intelligent manufacturing workstation. The NOODLES modeleris discussed by GURSOZ et al., in “Boolean Set operations onnon-manifold boundary representation objects,” in Computer Aided Design,Butterworth-Heinenmann LTD., Vol. 23, No. 1, January, 1991, the contentof which expressly incorporated by reference herein in its entirety TheNOODLES system makes far fewer assumptions about what constitutes validedge topologies, and thus overcomes problems with other modelingsystems, which would enter into infinite loops when the edge topology ofa geometric model would violate system assumptions.

6. Term Definitions

For purposes of clarification, and to assist readers in an understandingof the present invention, the following terms and acronyms used hereinare defined.

bending apparatus/bending workstation—a workstation or apparatus forperforming modern sheet metal working functions, including bendoperations.

bending sheets of malleable material—working of sheets of malleablematerial, such as sheet metal, including, and not limited to, up-actionair bending, V bending, R bending, hemming, seaming, coining, bottoming,forming, wiping, folding type bending, custom bending, and so on.

operations plan—a sequence of operations to be performed by a partforming apparatus in order to form a finished part from a piece ofunfinished material. In the context of bend sequence planning, anoperations plan (bend sequence plan) comprises a sequence of operationsto be performed by a bending apparatus for bending workpieces comprisingsheets of malleable material, the sequence of operations including abend sequence which includes all of the bends needed to form a finishedbent workpiece.

subplan—a portion of a complete operations plan. In the context of bendsequence planning, a subplan comprises a part of the information neededto set up and/or control a bending workstation/apparatus.

SUMMARY OF THE INVENTION

In view of the above, the present invention, through one or more of itsvarious aspects and/or embodiments, is thus presented to bring about oneor more objects and advantages, such as those noted below.

Generally speaking, it is an object of the present invention to providean intelligent bending workstation environment/system which may beeasily upgraded and integrated with additional or alternate hardware andsoftware modules. A further object is to provide such a system which canbe used to economically produce very small batch sizes (of one or moreworkpieces) with high quality, and in a short amount of time. Inaddition, an object is to provide such a system that is flexible andthat is able to accommodate new and different part styles in the designand manufacture process. The system of the present invention is intendedto operate efficiently in large volume production, and to learn frominitial production runs in order to maximize efficiency.

An additional object of the invention is to maintain quality of theproduced parts throughout the process, and to avoid errors andcollisions during execution of the process by the bending workstations.It is a further object of the present invention to provide anintelligent sheet metal bending workstation which makes small batches ofsheet metal parts from CAD descriptions. In this regard, a processplanner is provided that selects the necessary hardware (e.g., dies,punches, grippers, sensors) to be utilized by the bending workstation,determines bending sequences, and generates the necessary software tooperate the bending machine.

It is a further object of the present invention to provide such anintelligent, automated bending workstation which first generates aprocess plan and then executes the generated plan using a real-timesensor-based control method. When the process is executed, the resultsthereof may be recorded for later review, so that the process may berefined to make it more efficient, and to reduce the occurrence oferrors during execution.

An additional abject of the present invention is to provide a systemwhich can produce a plan for bending a sheet metal workpiece, in whichthe smallest number of tooling stages will be utilized to make the part.A further object is to provide a system that will efficiently andautomatically produce the plan to be utilized by the bendingworkstation, set up the workstation, and execute the plan.

The present invention, therefore, is directed to several systems,methods and sub-components provided in connection with a system forgenerating a plan which comprises a sequence of operations to beperformed by a bending apparatus for bending workpieces comprisingsheets of malleable material. The bending apparatus has a gripper forgripping a workpiece while performing a bend, and the sequence ofoperation includes a set of N bends for forming a finished workpiecefrom a stock sheet of malleable material. The system includes aproposing mechanism for proposing, for an mth operation within thesequence of operations, a plurality of proposed operations including aplurality of proposed bends to be performed by the apparatus. Inaddition, the system includes a subplan mechanism for providing aproposed subplan that accompanies each proposed bend, and a generatingmechanism for generating a plan including a sequence of bends from afirst bend through an Nth bend, by choosing each bend in the sequence ofoperations based upon the proposed bends and the proposed subplan thataccompanies each proposed bend.

The proposing mechanism may be designed so that it proposes bends amongthe complete set of N bends that are still remaining, or proposes bendsamong the complete set of bends that a still remaining less bends blockdue to constraints. In addition, the proposing mechanism may propose,for an mth operation, a repositioning of a gripper's hold on theworkpiece.

In accordance with a specific aspect of the invention, the generatedplan further includes at least part of the proposed subplans thataccompany the chosen bends. The system may further include a mechanismfor representing the mth operation as an mth level of a search tree. Theproposed subplans may include setup and control information for thebending apparatus, and may further comprise final locations on theworkpiece at which the gripper will grip the workpiece while performingthe bends of the bend sequence. The proposed subplans may furtherinclude ranges of locations on the workpiece at which the gripper cangrip the workpiece while performing the bends of the bend sequence. Inaddition, the proposed subplans may comprise: numbers representing apredicted number of repositionings of the gripper needed to complete thesequence of bends, indications that the next bend in the sequence cannotbe performed unless the gripper is first repositioned, and/or locationson the workpiece at which a repositioning gripper (i.e., a repo gripper)will grip the workpiece while performing a repositioning operation.Additionally, the proposed subplans may include: tooling stages to beutilized to perform the bends in the bend sequence, positions along atooling stage at which the workpiece will be loaded into the bendingapparatus in order to perform the bends, and/or motion plans formaneuvering around tooling stages in performing the bends.

In accordance with a further aspect of the system, an estimating deviceis provided for estimating a cost to be associated with each proposedbend. In this regard, the generating mechanism may generate a planincluding a sequence of bends from a first through an Nth bend, bychoosing each bend in the sequence of operations based upon the proposedbend, the proposed subplan that accompanies each proposed bend, and theestimated costs associated with each proposed bend. The estimated costsassociated with an nth bend in the sequence of N bends may comprise a kcost calculated based upon an estimated amount of time it will take thebending apparatus to complete one or more operations of the bend. Theestimated costs associated with an nth bend in a sequence of N bends maycomprise an h cost calculated based upon an estimated total amount oftime it will take the bending apparatus to complete one or moreoperations of each of the rest of the bends in the bend sequence thatfollow the nth bend.

The one or more operations of the bend which will be timed in order tocalculate the k and h costs may comprise moving the workpiece from atooling stage location of a preceding bend to a tooling stage locationof the given bend. The one or more operations of a given bend may alsocomprise installing, when setting up the bending apparatus, anadditional tooling stage needed to perform the given bend. The one ormore operations of a given bend may also comprise repositioning of thegripper's hold on the workpiece before performing the given bend.

In accordance with a further aspect of the present invention, theproposing mechanism and the generating mechanism collectively comprise abend sequence planning module, and the subplan mechanism and theestimating mechanism collectively comprise a plurality of expertmodules. The expert modules may each operate the subplan mechanism andthe estimating mechanism when the proposing mechanism proposes aproposed operation for performance as the mth operation within thesequence of operations. The plurality of expert modules may comprise aholding expert module which is capable of operating the subplanmechanism to provide a proposed subplan, including information regardinga location on the workpiece at which the gripper can hold the workpiecewhile performing the bends of the bend sequence. The plurality of expertmodules may comprise a holding expert module which is capable ofoperating the estimating mechanism to estimate a holding cost,calculated based upon whether a gripper's hold on the workpiece is to berepositioned before performing a given bend. In addition, the pluralityof expert modules may comprise a tooling expert module which is capableof operating the subplan mechanism to provide a proposed tooling subplanthat includes information regarding a position along a tooling stage atwhich the workpiece will be loaded into the bending apparatus in orderto perform a given bend. The tooling expert may also be capable ofoperating the estimating mechanism to estimate a cost based upon anamount of time to install, when setting up the bending apparatus, anadditional tooling stage needed to perform a given bend. The motionexpert module may also be capable of operating the estimating mechanismto estimate a cost based upon a calculated travel time for moving theworkpiece from a tooling stage location of one bend to a tooling stagelocation of a next bend.

In accordance with an additional aspect of the invention, the bendsequence planning module may be capable of querying each of the expertmodules for a subplan and estimated costs. In addition, each of theexpert modules may be capable of responding to a query by returning asavelist to the bend sequence planning module, whereby the savelistincludes a list of names of attributes, and values respectivelycorresponding to the attributes, to be saved by the bend sequenceplanning module.

As a further aspect of the invention, the system includes a prioritizingmechanism for prioritizing proposed bends in accordance with bendheuristics determined based upon the geometry of the workpiece. Thegenerating mechanism may generate a plan, including a sequence of bendsfrom a first through an Mth bend, by choosing each bend in the sequenceof operations based upon the prioritized proposed bends and the proposedsubplan that accompanies each proposed bend. The prioritizing mechanismmay be provided with a mechanism for discounting an estimated cost of abend having a high priority and increasing an estimated cost for a bendhaving a low priority.

In accordance with a further aspect of the invention, a determiningmechanism may be provided for determining the time needed for, and thefeasibility of, producing one or more parts with the bending apparatusbased upon the generated plan. In addition, the system may be providedwith a mechanism for performing calculations of the costs of producing agiven batch of parts, based upon the time determined by the determiningmechanism. In addition, or in the alternative, the system may beprovided with a mechanism for redesigning the part based upon the timeand the feasibility determinations made by the determining mechanism.The system may be further provided with a mechanism for schedulingmanufacturing with the bending apparatus depending upon the determinedamount of time for producing one or more parts.

In addition to the above-described system, the present invention isfurther directed to a computerized method for selecting a gripper forholding a workpiece. The gripper is selected for use in a bendingapparatus for bending unfinished workpieces comprising sheets ofmalleable material. The method includes reading information describingthe geometry of a library of grippers to be chosen from, forming a setof available grippers excluding grippers that have certain undesiredgeometric features, and choosing a gripper from a set of availablegrippers. The gripper is chosen as a function of the width of thegripper, the length of the gripper, and the knuckle height of thegripper. The gripper may include a gripper for holding the workpiecewhile loading and unloading the workpiece into and from a die space ofthe bending apparatus. In this regard, the method may include a step ofpredicting, for each gripper within the set of available grippers, arepo number equal to an estimated number of times the bending apparatuswill need to change the position at which the gripper is holding theworkpiece in order to perform a complete sequence of bending operationson the workpiece. The smallest predicted repo number is then determined,and the set of available grippers is adjusted to include the availablegrippers having a repo number equal to the smallest predicted reponumber, before choosing (from among the set of available grippers) agripper as a function of the gripper's width, length, and knuckleheight.

The gripper may alternatively comprise a repo gripper for holding theworkpiece while a robot changes its grip on the workpiece. In thisregard, the method may be further provided with a step of constructingdata representations of the respective intermediate shapes of theworkpiece when repo operations are to be performed by the bendingapparatus, and utilizing the intermediate shapes to determine whichgrippers are excluded from the set of available grippers. The grippersthat cannot securely grasp the workpiece, considering all of theconstructed intermediate shape representations, are excluded from theset of available grippers.

In addition to the above-described system and method, the presentinvention is further directed to a computerized method for determining alocation at which a gripper can hold a malleable sheet workpiece while abending apparatus performs an mth operation on the workpiece. Thebending apparatus performs a sequence of operations, including the mthoperation, in accordance with a bending plan. The sequence of operationsincludes a sequence of bends from a first bend through an Nth bend, andthe shape of the workpiece changes to several intermediate shapes as thebending apparatus progresses through the sequence of bends. A set oftopographic representations is formed by repeatedly generating, alongedges of the workpiece, as a variable i is varied, a graphicrepresentation of areas on the workpiece within which the gripperlocation can be without hindering performance of an ith operation. Adetermination is made as to whether or not the performance of the ithoperation will be hindered by taking into consideration the intermediateshape of the workpiece when the ith operation is performed. The methodfurther includes the step of determining the intersection of all thegeographic representations within the set to thereby determine the areascommon to the given plurality of operations in the sequence ofoperations. The mth operation may include changing a robot's grip on theworkpiece between bends in the sequence of bends, and/or performing abend within the sequence of bends.

In addition to the above, the present invention may be directed to acomputerized method for selecting tooling to be used in a bendingapparatus for bending a workpiece comprising a sheet of malleablematerial. The tooling includes at least a die and a punch, and thebending apparatus performs, utilizing the selected tooling, a sequenceof operations comprising a sequence of bends from a first bend throughan Nth bend. The method comprises steps of reading informationdescribing in the geometry of dies and punches, and forming sets offeasible dies and punches excluding dies and punches that have aninsufficient force capacity to bend the workpiece and that are incapableof forming desired bends in the workpiece resulting in desired anglesand desired inside radii. In addition, the method includes a step ofchoosing an appropriate die and appropriate punch that most closelysatisfies force, bend angle, and inside radii requirements, excludingpunches that will likely collide with the workpiece as determined byfailure of a geometric collision test.

The geometric collision test may be performed by modeling a finished 3Dworkpiece and, for each bend in the sequence of bends, aligning themodeled finished 3D workpiece between a model of each feasible punch anda model of a chosen die.

In addition to the above, the present invention may be directed to acomputerized method for determining a layout of tooling stages along adie rail of a bending apparatus. The bending apparatus is adapted tobend workpieces comprising sheets of malleable material, by performing asequence of operations comprising a sequence of bends from a first bendthrough an Nth bend. The method includes a step of deciding on anarrangement of a plurality of stages along the die rail and calculatinglateral limits based upon the amount by which the workpiece extendsbeyond a side edge of a tooling stage for the bends of the sequence ofbends. In addition, the method includes determining a largest laterallimit for each side of the stage, and spacing adjacently arranged stagesto have a gap between adjacent side edges that is greater than or equalto the larger of the determined largest lateral limits of the adjacentside edges.

In addition to the above-described system and methods, the presentinvention may be directed to a system for generating a plan and forcontrolling a bending apparatus. As described above, the plan comprisesa sequence of operations to be performed by the bending apparatus, andthe bending apparatus is adapted to bend workpieces comprising sheets ofmalleable material. The sequence of operations includes a sequence ofbends, from a first through an Nth bend, for forming a finishedworkpiece from a stock sheet of malleable material. The system includesa setup planning mechanism for generating the sequence of bends and asetup subplan that includes information regarding the manner in whichthe bending apparatus is to be set up before commencing the first bendin the sequence of bends. In addition, the system includes a forwardingmechanism for forwarding the setup subplan, once generated, to asignalling device for signalling commencement of setup operations to beperformed in accordance with the setup subplan. A finalize mechanism isfurther provided for generating detailed subplan information to completethe plan after the setup subplan has been generated. At least part ofthe detailed subplan information is generated after the commencement ofsetup operations has been signalled by the signalling device. The setupsubplan may include one or more of the following types of information:information regarding the layout of tooling stages; informationregarding tooling die and punch profiles to be utilized in the bendingapparatus; positions of tooling stages along a die rail of the bendingapparatus; information regarding what type of gripper to use formanipulating the workpiece through the bend sequence; and informationregarding what type of repo gripper to use for holding the workpiecewhile a gripper changes it grasp on the workpiece in between bends ofthe bend sequence.

The forwarding device may include a device for forwarding instructionsto a sequencer module which directs performance of automated setupoperations on the bending apparatus. In addition, or in the alternative,the forwarding device may also, or in the alternative, create a visualrepresentation of setup operations to be performed on the bendingapparatus so that a human operator can thereby perform the setupoperations.

In addition to the above-described systems and methods, the presentinvention may be directed to a system for performing setup operations ona bending apparatus so that the bending apparatus can be utilized toperform bending operations on workpieces comprising sheets of malleablematerial. The bending apparatus includes a die, a tool punch holdingmechanism, and one or more tooling stages. Each tooling stage includes adie mounted on the die rail and a tool punch held by the punch holdingmechanism. The system further includes a mechanism for receivinginformation regarding a location of each of the one or more toolingstages along the die rail, and a control mechanism for controlling aposition of a guide member along at least one of a die rail and the toolpunch holding mechanism based upon the received information so that atleast one of the die and the tool punch can be aligned with reference tothe guide member and so that the resulting tooling stage will be at adesired location along the die rail.

The control mechanism may be capable of positioning the guide member tobe at a specified position along the die rail and to be within a certaindistance from the die rail, whereby a die of a tooling stage to bealigned can be abutted against the guide member in order to properlyposition the tooling stage along the die rail. The guide member mayinclude a backgage finger of a mechanism for performing backgaging whenloading a workpiece into the bending apparatus.

In addition to the above-described Systems and methods, the presentinvention may be directed to a system for executing a plan forcontrolling a bending apparatus for bending workpieces comprising sheetsof malleable material The plan includes a sequence of operations to beperformed by the bending apparatus. A sensor-based control mechanism isprovided for performing an operation, including moving a workpiece fromone position to another, with the bending apparatus utilizing a sensoroutput to modify the movements of the workpiece. A measuring devicemeasures an amount by which the movement of the workpiece was modifieddue to the sensor output, and a learned control mechanism performs theoperation, including moving the workpiece from one position to another,without modifying the movement of the workpiece utilizing a sensoroutput. The learned control mechanism controls performance of theoperation based upon the amount measured by the measuring device.

The above-listed and other objects, features, and advantages of thepresent invention will be more fully set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is further described in the detailed descriptionwhich follows, by reference to the noted plurality of drawings by way ofnon-limiting examples of illustrative embodiments of the presentinvention, in which like reference numerals represent similar partsthroughout the several views of the drawings, and wherein:

FIG. 1 illustrates a prior art bending workstation;

FIG. 2 illustrates part of a side view of a prior art bend press;

FIG. 3 illustrates a partial front view of a prior art bend press;

FIG. 4 illustrates a prior art bend planning and control system;

FIG. 5A illustrates a bend planning and control system provided inaccordance with an illustrated embodiment of the present invention;

FIG. 5B illustrates a stage setup controlling system;

FIG. 5C illustrates a top view of a die rail with a stage setupoperation being performed thereon;

FIG. 6 illustrates a bend planing and control system with a detaileddiagram of control system 75 as illustrated in FIG. 5A;

FIG. 7 illustrates a high level flow chart of an overall planningprocess to be performed by the illustrated planning system;

FIG. 8 illustrates a flat workpiece provided for purposes of describinglabeled geometric bend-related features;

FIG. 9 illustrates a flat workpiece and a corresponding search tree;

FIG. 10 illustrates a thickness transformation of a single workpiece;

FIG. 11 illustrates a thickness transformation of an assembly ofworkpieces;

FIG. 12 illustrates a geometric modeling file structure with and withouta thickness transformation;

FIG. 13A illustrates a plurality of functions of a design system forintelligent bend planning;

FIG. 13B illustrates a part modeler for modeling parts based upon adesign system's output shape file;

FIG. 13C and FIG. 13D respectively illustrate a 2D representation and a3D representation of a workpiece;

FIGS. 14A-14E illustrate an example graphic user interface of the CADsystem provided in the illustrated embodiment, and the steps ofdesigning a part utilizing such a graphic interface;

FIG. 15A illustrates a side view of a bent workpiece with thickness;

FIG. 15B illustrates a top view of an undeveloped flat 2D workpiecerepresentation;

FIG. 15C illustrates a top view of a developed flat 2D workpiecerepresentation;

FIG. 16 illustrates a 2D drawing corresponding to a bend graph listing;

FIG. 17A illustrates a BM100 geometric modeling filing structure;

FIG. 17B illustrates a tooling modeling file structure;

FIG. 18A illustrates a gripper modeling file structure;

FIG. 18B illustrates a part modeling file structure;

FIG. 19 illustrates an FEL planning message to be sent from a bendsequence planner to a motion expert;

FIG. 20A presents an example of a workpiece and a search tree generatedin accordance with the workpiece;

FIG. 20B illustrates an example workpiece and search tree with bend twinnodes;

FIG. 20C illustrates an example workpiece and search tree with aconstrained bend twin node;

FIGS. 20D and 20E illustrate example workpieces with co-linear bends;

FIG. 21 illustrates a general example flow chart of A* applied to sheetmetal bending;

FIGS. 22A-22D illustrate the main flow of an embodiment of the bendsequence planner illustrated herein;

FIGS. 23A-23D illustrate a process for performing subplanning and costassignment;

FIG. 24 illustrates an example workpiece and search, tree, withcalculated costs illustrated;

FIG. 25A is an example workpiece having an inner tab;

FIG. 25B is an example workpiece with outer and inner bend lines;

FIG. 25C is an example workpiece with short and long bend lines;

FIG. 25D is an example portion of a bent workpiece, with abutting insideand outside corner edges;

FIG. 25E represents an example cutaway portion of a workpiece withco-linear bends;

FIGS. 26A, 26B, 27A-27C show example workpieces used to explainconstraint expressions;

FIG. 28 comprises a graph comparing the histories of nodes b6′ and b6;

FIG. 29 comprises a chart of a dialogue between the bend sequenceplanner and the holding expert;

FIG. 30 illustrates a chart of a dialogue between the bend sequenceplanner and the tooling expert;

FIG. 31 illustrates a chart of a dialogue between the bend sequenceplanner and the motion expert;

FIG. 32 illustrates a process of the selection of a robot gripper;

FIG. 33A illustrates a flat 2D workpiece with discretized x pointsillustrated thereon;

FIG. 33B illustrates a bent 3D workpiece with discretized x pointsplaced thereon;

FIGS. 34A-34B illustrate a process for predicting a minimum number ofrepos to be performed before the search;

FIGS. 35A-35B illustrate a process for predicting a minimum number ofrepos to be performed during the search;

FIGS. 36A-36B illustrate a process for determining the robot's grasplocations on the workpiece;

FIG. 37 illustrates a 2D workpiece having both sheet and edge coordinatesystems;

FIG. 38 illustrates a 2D workpiece and the illustrated generation ofavailable Y grasp locations;

FIG. 39 is a diagram representing the intersections grasp regions todetermine of a final grasp region before a repo is performed;

FIG. 40 comprises examples of grasp regions in different levels of thesearch;

FIG. 41 illustrates a process for determining the repo gripper location;

FIG. 42 illustrates a process for selecting a repo gripper beforeperformance of a state-space search;

FIGS. 43A-43B illustrate a process for selecting a repo gripper to beperformed after a state-space search;

FIG. 44 illustrates a bin-packing process to be performed before asearch;

FIG. 45 illustrates a graphic representation of the steps utilized todetermine an initial tooling h-cost (based upon the total predictedstages which will be needed to perform the complete bend sequence);

FIG. 46 illustrates the steps of a process for determining the initialtooling h-costs;

FIG. 47A illustrates a process of selecting tooling to be used;

FIGS. 47B-47C illustrate a process for performing stage planning;

FIGS. 48A-48C are graphic representations of a modeled bend press andworkpiece which will be utilized during stage planning;

FIG. 49 illustrates a process of fine motion planning;

FIG. 50 illustrates process steps performed by the motion expert tocalculate k and h costs;

FIG. 51 is a graphic representation of models of a bend press, a robot,and a workpiece, the models being used for determining a gross motionplan;

FIG. 52 is a block diagram which illustrates the structure of thecontroller software of the planning system illustrated herein;

FIG. 53 illustrates the main process steps of the sequencer taskprovided within the sequencer of the placing system illustrated herein;

FIG. 54 illustrates the steps performed in executing a bend inaccordance with a developed plan;

FIG. 55 illustrates a robot task which forms part of the control system;

FIG. 56 illustrates a press and loader/unloader (L/UL) task of thecontrol system;

FIG. 57 illustrates a backgage task of the control system; and

FIG. 58 is a flow chart demonstrating the main steps performed in alearning process that may be performed by the planning systemillustrated herein.

BRIEF DESCRIPTION OF THE APPENDICES

The present invention is further exemplified by a plurality of listingswhich are provided in the Appendices, wherein:

Appendix A is an output shape file produced by a CAD system whichincludes a geometric/topological data structure of a workpiece asillustrated in FIG. 14E;

Appendix B comprises an example bend graph listing formed from thegeometric/topological data structure provided in the listing of AppendixA;

Appendix C is an exemplary listing representing the FEL messages thatmay be generated and forwarded between the bend sequence planner andvarious experts during the planning process; and

Appendix D is an example specification for a listing which representsthe final plan in FEL which is forwarded from bend sequence planner tothe sequencer of the planning and control system 71 illustrated herein.

DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS

1. Planning, Setup and Control

Referring now to the Figures in greater detail, FIG. 5 illustrates ablock diagram of an embodiment of a planning and control system 70 foran intelligent manufacturing bending workstation. In the illustratedembodiment, planning and control system 70 includes a CAD system 74, abend sequence planner 72, a plurality of experts (sub-planners), and asequencer 76. Planning and Control System 70 is connected to hardwareand sensors 78 via an interface 77.

The experts include a tooling expert 80, a holding expert 82 and amotion expert 84. Additional experts may be provided, such as sensingexpert 85 illustrated in dotted lines. Bend sequence planner 72, experts80, 82, and 84, and CAD system 74 may be implemented within aUNIX-compatible environment on a workstation computer such as a Sparc 10Sun OS v.4.1.3. Sequencer 76 may be implemented within an additional CPUcoupled to the Sun workstation via a bus adaptor. The bus adaptor maycomprise a BIT 3 VME-to-VME bus adaptor which extends between the Sunworkstation and a remote VME bus passive back-plane. The passiveback-plane may hold several interface mechanisms such as VME (VirtualMemory Extension) boards, which together form part of interface 77 asillustrated in FIG. 5. Sequencer 76 may be implemented within areal-time UNIX-compatible multiprocessor operating system such asCHIMERA, and may be run by the additional CPU which is provided in thecomputer workstation's back-plane. Accordingly, in the illustratedembodiment (shown in FIG. 5), CAD system 74, bend sequence planner 72,experts 80, 82, 84 (and 85) and sequencer 76 are each implementedprimarily with software which controls the operations of a computerutilizing a UNIX-compatible operating system. Sequencer 76 isimplemented within a real-time UNIX-compatible multiprocessor operatingsystem such as CHIMERA.

CAD system 74 is utilized to design a sheet metal configuration, bydefining the shape of a stock (flat) sheet metal part and the bends tobe performed on the stock part to form a desired three-dimensionalfinished part. In designing the sheet metal part, CAD system 74 formsone or more information files which describe the part. As athree-dimensional part is designed, in a preferred embodiment, the CADsystem maintains in memory, and visually, a three-dimensionalrepresentation of the sheet metal part in parallel with atwo-dimensional representation of the part. The designer may modify thedesign by adding or removing details to or from either representation.CAD system 74 may also perform functions such as gathering and/orgenerating information needed for geometric modeling and requestingadvice from bend sequence planner 72 as to whether certain designfeatures can be implemented by the bending workstation.

Bend sequence planner 72 operates in cooperation with tooling expert 80,holding expert 82, motion expert 84, and any other experts (e.g.,sensing expert 85) to produce a plan for complete part production by abending workstation of the part designed with the use of CAD system 74.Bend sequence planner 72 performs functions such as proposing aparticular bend in a hypothetical bend sequence, and determining whatinitial steps must be performed by the system in order to execute such abend having a position within the hypothetical bend sequence. Indetermining the consequences of the proposed bend, bend sequence planner72 may query tooling expert 80 as to what tooling would be needed toexecute the proposed bend, querying holding expert 82 as to how theworkpiece can he held while performing the proposed bend, and queryingthe motion expert 84 as to whether and to what extent the robot (whichis holding the workpiece) can be manipulated to assist in making thebend. If a sensing expert 85 is provided, bend sequence planner 72 mightquery sensing expert 85 as to whether a particular sensor-based controlstrategy is needed in order to facilitate the execution of the proposedbend by the workstation and the costs associated with a particularsensor-based control strategy. Bend sequence planner 72 may beconfigured to continually propose bends from a first bend consecutivelyto a last bend in a complete bend sequence, thus resulting in a completeset of bends to perform the final workpiece. Once the successful finalbend sequence has been generated in this manner, bend sequence planner72 may be configured to generate a final plan (which includes a generallist of steps and accompanying information needed to control executionof the various hardware elements of the workstation), and forward theplan to sequencer 76.

Sequencer 76 directs execution of the plan developed by bend sequenceplanner 72. Sequencer 76 interprets commands given by bend sequenceplanner 72 in the resulting plan, and controls timing of the variouscommands by parsing the commands and information accompanying thecommands and placing them into queues provided for each of the mainhardware elements of the sheet metal bending workstation.

Controller 75 comprises a plurality of tasks which correspond to thevarious hardware elements of the workstation. Each task is activated bythe sequencer in an appropriate manner in accordance with the planforwarded by the planner.

(a) The Planning System Operations: Planner and Sub-planners

Bend sequence planner 72, and the several sub-planners including, e.g.,tooling expert 80, holding expert 82 and motion expert 84, (and sensingexpert 35), form a planning system 71.

Bend sequence planner 72 analyzes the designed part (Sheet metalworkpiece), provided by CAD system 74, and offers a bend sequence to beperformed by the bending workstation. Planner 72 utilizes a state-spacesearch method in order to determine an efficient sequence of bendoperations that can be utilized by the bending workstation. Planner 72converses with tooling expert 80, holding expert 82 and motion expert 84in order to obtain the information it needs to make its decisions.

Tooling expert 80 responds to queries made by planner 72, and providesinformation to the bend sequence planner such as which tools will beneeded for a particular bend operation or bend sequence. In addition,tooling expert 80 may inform bend sequence planner 72 of the arrangementof tools within the workstation. Tooling expert, in conjunction withplanner 72, will attempt to design a setup of tooling so that the fewestnumber of stages/toolings are utilized to make a particular part, i.e.,to execute a complete bend sequence for making the part.

Holding expert 82 makes holding-related determinations such as, e.g.,whether the robot can hold the workpiece while a particular bend,specified by bend sequence planner 72, is being performed. Holdingexpert 82 may also determine the location at which the robot should holdthe workpiece so that the workpiece may be maneuvered through a seriesof bends, without collision, and without the need to change the robot'sgrasp on the workpiece. In addition, holding expert 82 may determine theposition at which the repositioning gripper should hold the workpiecewhen the robot's grasp is being changed, and where suction cups 31 ofloader/unloader (L/UL) 30 should be placed during unloading and loadingof the workpiece.

Motion expert 84 is responsible for generating a motion plan, i.e., themanner in which the robot should be maneuvered in order to move theworkpiece through various spaces and along various routes as needed toexecute the bends.

Bend sequence planner 72 and the respective experts may be modular tocommunicate with each other in a query-based manner. For example, beforedeciding to include a particular bend as part of the bend sequence, bendsequence planner 72 may query tooling expert 80 as to whether there aresufficient tools to handle the bend. Bend sequence planner 72 will thenawait a response from tooling expert 80. Tooling expert 80 willrecognize the query from bend sequence planner 72, and will return witha response, e.g., indicating that there are sufficient tools to handlethat particular bend noted by bend sequence planner 72. By way ofexample, bend sequence planner 72 may also ask holding expert 82 ifrobot arm gripper 14 can remain holding onto the workpiece during aparticular bend operation without repositioning its grasp of theworkpiece. Holding expert 82 will then respond to the query made by bendsequence planner 72, and bend sequence planner 72 will then utilize theinformation to perform its next determination.

Each of the modules of planning system 71 utilizes one or more functionsprovided by a geometric modeling library (not shown) in order to modelthe relative interactions and positions of each of the hardwarecomponents of the system as may be needed in making theirdeterminations.

(b) System Setup

Once a plan is generated by the planning system, the system will performa setup process. The setup process can be performed completely manually,or it may be automated in full or in part with the use of automated toolchangers. The manual activities to be performed during the setup processmay include downloading program data to dedicated controllers such asthose illustrated in FIG. 1.

As shown in FIG. 5C, each stage (stage 1 and stage 2 as illustrated inFIG. 5C) must be set up by placing a plurality of die segments 810 a,810 b, and 810 c in stage 1, and 811 a, 811 b, and 811 c for stage 2along die rail 22. In order to gauge the location at which die segmentsfor each stage will be placed, a human operator will typically measurethe distance from the edge of the die rail 22 to a particular edge ofthe die corresponding to each stage. For example, a measurement may bemade from the left edge of die rail 22 to the left edge of each die setfor each stage in order to position the die segments corresponding toeach stage. Pursuant to a particular embodiment of the presentinvention, a mechanism may be provided for automatically providing aguide that can be used by the setup operator to place the die segmentsat the appropriate location along die rail 22. Such a mechanism maycomprise a backgage finger 88 which can be automatically positioned at aparticular edge of each stage along die rail 22. For example, backgagefinger 88 may be first located at location A for purposes of abuttingfirst die segment 820 a against backgage finger 88, and subsequentinstallment of second and third die segments 810 b and 810 c. Afteraligning die segments for stage 1, backgage finger 88 may beautomatically positioned to the next stage, i.e., stage 2. Moreparticularly, backgage finger 88 may be positioned at one side of thedie corresponding to stage 2. In the illustrated example, backgagefinger 88 is positioned at the left edge of die 811 While backgagefinger 88 is at that position, first die segment 811 a may be placedalong die rail 22 and abutted against backgage finger 88 for alignment.Thereafter, die segments 811 b and 811 c may be placed on and secured todie rail 22

FIG. 5C illustrates the main components for controlling the backgagefinger 88 to assist in positioning an alignment of dies 810 and 811. Thesubsystem comprises an input control module 87 a which includes amechanism for instructing backgage servo controller 87 b to movebackgage finger 88 to one or more particular stage locations.

According to FIG. 5A, alignment control module 87 a may be provided incontrol portion 75 of planning and control system 70, while backgageservo controller 87 b may be provided with an interface 77. Morespecifically, controller 75 may be provided with a backgage task module.The backgage task module may be provided with a backgage fingerdie-alignment function which may be called by the backgage task module.In calling the die-alignment function, the backgage task module mayactivate and control a backgage servo controller through the use of asecond level backgage device driver 206 (see FIG. 6), which in turninteracts with an appropriate level 1 device driver such as an I/Odevice driver 220 which interacts with a parallel I/O card connected tothe backgage hardware of the bending workstation.

Another manual step that can be performed is positioning and/oradjusting of the punch holders 20. In addition, standard steps may beperformed to align tool punch segments so that they are properly seatedwithin each punch holder 20 and correspond to the associated diesegments. This may comprise operating the press so that the die segmentsand corresponding tool punch segments are compressed against each otherwith a set amount of force. In addition, other standard adjustments andprocedures, known to those skilled in the art, 30 may be performedduring setup. For example, loader/unloader may need to be adjusted sothat suction cups 31 are properly positioned with respect to theworkpiece 16.

Workstation 10 may be configured to be controlled automatically by theplanning system, without any need for human intervention. In the eventthat certain control modules are still maintained as separate, e.g.,separate robot control module 44 as shown in FIG. 1, along with separatepress brake controller 42 and load/unload controller 46, the planningsystem may be configured to download appropriate components of the planto the appropriate control modules.

(c) Sequencing and Control

In the illustrated embodiment, sequencer 76 is implemented within areal-time UNIX-compatible shell such as an Ironics IV-3230 computer witha CHIMERA II operating system. Additional information regarding possibleimplementations of a real-time scheduler such as sequencer 76 isprovided in the CHIMERA manual by Stewart, Schmitz and Khosla, entitled“CHIMERA II Real-Time Programming Environment, Version 1.02” (Oct. 29,1990), the content of which is incorporated by reference herein in itsentirety.

Sequencer 76 schedules the general execution of the generated plan bycontrol system 75, which utilizes interface architecture 77 tocommunicate with various hardware elements and sensors within thesystem, depicted as hardware and sensors 78 in FIG. 5.

FIG. 6 depicts in greater detail, sequencer 76, control system 75, andinterface architecture 77. As illustrated in FIG. 6, sequencer 76 isconnected to bend sequencer planner 72 and is further connected to aplurality of modules which comprise control system 75. The modules ofcontrol system 75 include a robot task 92, a press and L/UL task 94, abackgage task 96, a motion library 98, a speed control module 102 and acollision detection module 100. Interface architecture 77 comprises aset of level 2 device drivers and another set of level 1 device drivers.The level 2 device drivers (DD's) may include robot DD 202, press andL/UL DD 204, backgage DD 206, gripper DD 208, gripper sensor DD 210,droop sensor DD 212, backgage sensor DD 214, and angle sensor DD 216.The level 1 device drivers may include respective device drivers 220,222 and 224 for one or more parallel I/O VME cards, one or more A/D VMEconverter cards, and a robot servo control card.

Accordingly, as illustrated by interface architecture 77, a two-leveldevice driver format is recommended for interfacing the various tasksand control modules of control system 75 to the various hardwareelements of the bending workstation. The first level device driverscomprise a UNIX-like interface, with commands supported includingopen(), close(), read(), write(), ioctl(), and mnap() commands. Thefirst level device drivers standardize the interface to the I/O ports towhich the hardware devices are attached, such as parallel I/O ports,analog/digital converters and a robot servo control mechanism. Thesecond level device drivers form an interface between the variousmodules of the control system 75 and the first level device driver.Although there is no standard interface routines provided for the secondlevel device drivers, the second level device drivers may be implementedwith the use of a standard form as disclosed in the above-noted CHIMERAmanual. With the use of a two-level device driver format, a softwareinterface system may be provided which is reliable, portable, and hascode which is easily readable. Specific details regarding the devicedrivers, and examples implementations thereof, are provided in theabove-noted CHIMERA manual, which has been incorporated by referenceherein.

As to the VME cards which are the actual I/O ports connecting thecomputer to the hardware elements, such cards may include, as notedabove, one or more parallel I/O cards, such cards preferably havingoptically isolated connections between the computer and the varioushardware elements connected thereto. In addition, the V cards mayinclude one or more Geonics motion two axis servo control cards II MCCIIand one or more A/D converters having sufficient a number of channelsand bit resolution, e.g., an A/D converter with 16 channels and 12 bitresolution, such as the IMV-1645 Ironics (Pentland-Burr-Brown MPV 950S).The parallel I/O cards may include an 80-channel (with 64 usablechannels) Xycom XVME-240 card and/or 32-channel digital output boardssuch as the Xycom XVME-220 and/or XVME-212 boards. One or more A/Dconverters can be provided for inputting information such as readingvarious data produced by the sensors included in the workstation, suchas a gripper sensor, droop sensor, backgage sensor, and/or angle sensor.

Each of the robot task 92, press and L/UL task 94, and backgage task 96,control the appropriate device drivers for controlling the correspondinghardware elements of the bending workstation. Several functions whichmust be performed during execution of various motion-related functionsmay be provided in motion library 98. Such functions may includekinematics, trajectory calculations and filtering. Any control functionsrelating to speed control, i.e., controlling the speed with whichvarious physical elements (such as the robot) of the bending workstationare moved, may be implemented within speed control module 102. Collisiondetection module 100 is provided in order to perform collision detectionwhich is needed in certain motion control processes during execution ofthe bend process.

Motion library 98 may further include dynamic motion control andsensor-based motion control modules which directly communicate with thesecond-level device drivers for dynamically controlling the movement ofvarious components of the bending workstation and for changing suchcontrol in accordance with sensor-based signals produced by the varioussensors provided in this system.

It is noted that in the parallel I/O cards, it is preferred that thecomputer be optically isolated from the actual hardware connections toprevent damage that may be caused by surges present at the hardwarecomponents. Other reasons for optically isolating the parallel I/O cardsis to protect the computer and the cards and to prevent the occurrenceof ground loops. However, it is not necessary that the A/D converters beoptically isolated from the sensors.

2. Bend Sequence Planner

Bend sequence planner 72 of the embodiment shown in FIG. 5A performsthree main functions. It generates a bend sequence, includingaccompanying operations associated with each bend, queries experts as tothe consequences of the bend sequence as it is generated, and as tofurther plan details (subplans) needed to accomplish the generated bendsequence, and compiles all gathered/generated information in order toform an overall plan. The plan specifies the steps needed to execute thebend sequence by a control system which controls operations of the sheetmetal bending workstation. Each of the experts of the illustratedplanning system 71 performs three main functions when requested byplanner 72. They each determine an incremental cost for performing anindividual step within the bend sequence, develop proposed/intermediateplan information, and communicate the incremental cost and planinformation to bend sequence planner 72. The proposed/intermediate planinformation includes two types of information: definite information andindefinite information. For example, at a certain point in time duringplanning, holding expert 82 will know which regions of the workpiece maybe grasped by the robot grasper to perform a given bend within a bendsequence (the grasp regions being definite), but will not yet know theexact grasp location (the precise grasp location being indefinite). Atemporary (indefinite) grasp location will be assigned by the holdingexpert 82, which can be verified at a later time. As noted above,sequence planner will query each expert as to the consequences of a bendsequence as it is generated.

The consequences of the bend sequence are represented in terms of cost.The costs of the bend sequence as it is generated may be determined as afunction of one or more of: the amount of time that it takes to performa particular operation within the bend sequence, the extent to which anoperation within the bend sequence will affect the accuracy of theoperation and the quality of the resulting workpiece, whether or notthere are any safety concerns associated with performing a particularoperation at a particular point in a bend sequence, and whether thereare any heuristics which, if taken into account, would suggestperforming one operation instead of another at a particular point in thebend sequence.

Bend sequence planner 72 may query experts for information such as whattool profile should be utilized to perform certain bends of the bendsequence, what stage segments will be needed to form a given stage whichwill be needed to perform a bend, and where can/should the robot grippergrasp the workpiece in performing one or more bends of the bendsequence. In addition, planner 72 may query the experts as to when arepositioning of the workpiece should be performed in the bend sequence,and how should the robot and the workpiece be moved in order to executevarious operations throughout the sequence, such as a bed,repositioning, workstation load, and/or a workstation unload. FIG. 7represents, in a high level flow chart, the major steps performed by anexample embodiment of bend sequence planner 72. In a first step S1,parallel design processing is performed by CAD system 74. The paralleldesign processing may comprise, among other functions, labeling variousgeometries corresponding to respective portions of the workpiece, theresulting labels being used later (in step S3) by the bend sequenceplanner to determine whether heuristics should be considered ingenerating the bend sequence plan. Subsequently, in step S2, aheuristics framework is produced to guide the-bend sequence planner inchoosing the bends that will form the bend sequence. In producing theheuristics framework for the bend sequence in step S2, a partial orderof bending steps is computed that complies with certain specifiedheuristics. Subsequently, in step S3 a state-space search algorithm isperformed which will be influenced by the heuristics framework. Thestate-space search algorithm performs an analysis of the implications ofperforming various bends in a prescribed order, by assigning costs toeach bend in step S4. In order to help with the assignment of costs, instep S5, geometric reasoning is utilized, e.g., to determine thephysical implications a particular bend will have by modeling themachine and the resulting workpiece as they relate to each other duringthe execution of each bend.

The heuristics are taken into account by either reducing the assignedcosts for a particular bend (if it is preferred due to heuristics) or byincreasing the assigned costs (if the bend is not preferred due toheuristics). A particular sequence of bends is thus developed in stepS3, which can be executed to produce the desired finished workpiece.Once the state-space search algorithm is performed in step. S3, adetermination is made in step S6 as to whether or not a complete plan,including a complete bend sequence, has been generated. If a plan cannotbe formed for the design that has been specified, the process returns tostep S1, where the workpiece may be redesigned to form a part design forwhich an operational plan can be created.

If a determination is made in step S6 that a complete plan was produced,the process will proceed to step S7, and the complete plan will beforward, using FEL, to the sequencer, or the plan may be stored in afile for later retrieval and execution by the sequencer. The state-spacesearch algorithm will preferably comprise an A* algorithm, such asdisclosed, e.g., by Nils J. Nilsson in “Problem-Solving Methods inArtificial Intelligence” McGraw-Hill Book Company, 1971, pages 43-67,the content of which is expressly incorporated herein by reference inits entirety.

It is noted that the cost assignment step 54 may consider variables suchas robot motion, gripping positions, the need for regripping, the needto change the gripper, tooling positions, and the need to change thetools. High costs are assigned for variables that will be timeconsuming, sacrifice quality, and/or expose the system to high risk.

The above-described operations planning method can be termed generativeplanning (since it automatically generates a bending plan), with weakheuristics and state-space searching. In performing the method, a humaninputs the design. A heuristics framework is defined using heuristicswhich are called “weak heuristics” because they comprise only a limitedset of rules. Possible bends are considered, and costs are assigned toeach considered bend. The costs assigned to the bends are influenced bythe heuristics framework by augmenting or discounting the cost of aparticular bend. A sequence of bends of the least total cost is chosenutilizing a state-space searching algorithm.

Generative planning with weak heuristics as disclosed herein should becontrasted with other approaches to operations planning. One suchapproach includes variant planning with case-based reasoning. In variantplanning, a human inputs a design of a new part, and the design is codedaccording to an index. The index is used to look up an old design whichbest resembles the current part to be designed and the problems to besolved. A human operator edits the old plan to solve the new problems,e.g., by editing an RML program. One of the problems noted with variantplanning is that a similar design may require different or divergentsolutions, which will not be discovered by comparison to old plans.

Another approach to operations planning is generative planning withstrong heuristics. With generative planning with strong heuristics, thehuman inputs the design and several labeled features of the new part.Heuristics are then used to determine the total ordering of bends andmachine operations, thus being called “strong heuristics.” A generativeplanning system with strong heuristics lacks the flexibility andintelligence of a generative planning system with weak heuristics, andwill likely be unable to handle unorthodox problems. Such a system hasno understanding as to what heuristics work better in a particularsituation, and which heuristics should be discarded. Moreover, such asystem will be incapable of developing a plan in many cases.

(a.1) Heuristics

Sheet metal bending heuristics can be taken into account by the bendsequence planner of the present invention. Several exemplary bendheuristics will be described as follows. One heuristic is to bendinternal tabs early. FIG. 25A illustrates a workpiece 16 having aninternal tab 33 which is to be bent along bend line 34 a. In accordancewith this heuristic, although there are other bends to be performedalong bend lines 34 b, 34 c, and 34 d, it is preferred that the internaltab 33 be bent along bend line 34 a first.

In accordance with another heuristic, it is desired that the bends alongthe outermost bend lines be performed before the bends along the innerbend lines. For example, referring to FIG. 25B, a workpiece 16 is shownwhich includes outer bend lines 35 a, 35 b, 35 c, and 35 d, along withinner bend lines 36 a, 36 b, 36 c, and 36 d. In this illustratedexample, in accordance with the heuristic, it is desired that the outerbends corresponding to outer bend lines 35 a-35 d be performed beforethe bends corresponding to inner bend lines 36 a-36 d.

In accordance with a third heuristic, it is preferred that shorter bendsbe performed before longer bends. FIG. 25C illustrates a workpiecehaving shorter bends along bend lines 37 a and 37 b, and longer bendsalong bend lines 38 a and 38 b. Accordingly, it is preferred that thebends along bend lines 37 a and 37 b be performed before the bends alongbend lines 38 a and 33 b.

In accordance with a fourth heuristic, it is preferred that bends whichform an outside face, of a corner of a 3D workpiece, be performed beforethe abutting inside corner fase. FIG. 25D illustrates a workpiece 16having an outside face 39 a and an inside face 39 b which each abut eachother at a corner 390. If the bend corresponding to the inside face wasdone first, then, when performing the bend corresponding to the outsideface 39 a, the press would not be able to cause the flange to be bentbeyond its intended 90° angle. Accordingly, when the outside facesprings back, it will not be flush with the end portion of inside face39 b.

In accordance with an additional heuristic, co-linear bends areperformed simultaneously. As shown in FIG. 25E, a workpiece 16 is shownto include two tabs 26 a and 26 b, which are each to be bent along bendlines 27 a, 27 b, respectively. Since the bend lines 27 a and 27 b areco-linear, in accordance with the heuristic, it is preferred that thebends along those bend lines will be performed simultaneously.

The above-described heuristics are only examples of the types ofheuristics which may be taken into account by the bend sequence plannerof the present invention. A larger or smaller set of heuristics,including all or a portion of the above-listed heuristics, may beutilized by the bend sequence planner.

In order to recognize when certain heuristics may apply to a givenworkpiece in developing the plan, a list of key features may be createdwhich describe various geometric features of the workpiece which canthen be utilized by the bend sequence planner in applying the heuristicrules. A list of key features may be described with respect to theexample workpiece 16 illustrated in FIG. 8. Several features may bededuced from workpiece 16, while it is still in its 2D state. An exampleof such features may include the flange number, the width of the flange,and the height of that flange. Referring, e.g., to flange 7, the flangenumber of the flange would be 7, a value w would be assigned to thewidth of that flange, and a value h would be assigned as the height ofthat flange. In addition, values may he defined which specify anangle-class, i.e., a class of flanges which all have the same bendangle.

Additional features which may be labeled to avoid extra searching in thesearch space include an indication that the part that is symmetricaround one or more axes.

FIG. 8 illustrates a workpiece 16 and a search tree 15 correspondingthereto. Workpiece 16 has an axis of symmetry Y which is divided downthe middle, running longitudinally through workpiece 16. Accordingly, atthe first level of the search, the nodes corresponding to bends 3 and 5have been eliminated (as indicated by the circles surrounding thesebends) because they are symmetrical with nodes 2 and 4. There is no needto also evaluate and search through bends 3 and 5 at the first level,since the same effective results would be obtained if the search startedwith the bend corresponding to those nodes as opposed to either of bends2 and 4. If the first bend chosen is bend 1, at the next level of thesearch, bends 2 and 4 are still symmetrical with bends 3 and 5. Thus,the nodes corresponding to bends 3 and 5 are again eliminated due to thefact that they are symmetrical with bends 2 and 4. However, if the nodecorresponding to bend 4 is the first chosen node in the sequence, thiseliminates the symmetry of workpiece 16. Thus, at the next level of thesearch stemming from the node of bend 4, there are no nodes eliminateddue to symmetry.

(a.2) Constraints

Depending upon the geometric features associated with a part to beformed, there may be bend-related operations which cannot be performedat certain points in the operations sequence being planned. Thesebend-related operations can be constrained to (or excluded from) certainlocations in the bend sequence by using a mechanism referred to as a“constraint”. A feature extraction module (not shown) may be provided toautomatically label geometric features from geometric models produced bythe design system (e.g., using data structures similar to thoseindicated above), and the geometric feature labels can be used to formlegal phrases (called constraints) in an interface communicationlanguage, such as FEL.

Constraints may be defined by using a data structure that allows aparticular arrangement of bend operations to be specified, in varyingdegrees of flexibility. For example, for a four-sided part 16 asillustrated in FIG. 26A, the following constraint statement can be usedto specify the order in which bends 1, 2, 3, and 4 are performed:

(constraints ((1 2 3 4)))

This statement signifies that the first bend must be performed beforethe second, which must be performed before the third, which must beperformed before the fourth. Further, since there are no operatorsincluded in the statement, there may not be any other bend operationsperformed before, between, or after any of bends 1-4.

If the bend 2 must be performed before bend 3, but there are no otherconstraints on the arrangement of the bend operations in the bendsequence, the following constraint statement may be used:

(constraint ((* 2 * 3 *)))

The operator “*” acts as a “wild card”, and allows either no bendoperations or any number of bend operations to be performed at itslocation in the bend sequence, and the type of bend operations which maybe performed at its location can be among any of the remaining bendoperations not specified in the constraint statement.

Another wild card operator, “?”, can also be used, and it signifies thatexactly one bend operation, among those not specified in the constraintstatement, must be performed at its location in the bend sequence. Thus,if precisely one bend operation must be performed before bend 2 in thepart shown in FIG. 26A, but there is no limitation on the number or typeof bend operations following bend 2 (except that they may not includebend 2), the following constraint statement can be used:

(constraint (( ? 2 * ))).

The constraint statements may also include grouping operators, whichrequire that certain bend operations be grouped together with nolimitation on the order of the bend operations within the group. Forexample, the following constraint statement requires that bends 2 and 3be before bend 4 in the bend sequence, and that bends 2 and 3 be groupedtogether with no bend operations therebetween:

(constraints ((* { 2 3 } * 4 * ))).

More than one constraint expression can be included within a constraintstatement. For example, the following constraint statement includes theabove grouping constraint expression, as well as an additionalconstraint expression which further specifies that bend 1 must be beforebend 4 without any additional limitations as to the inclusion andarrangement of the other operations with respect to bends 1 and 4:

(constraints (( * {2 3 } * 4 * ) ( * 1 * 4 * ))).

There can he any number of bend operations within a group, and groupscan be nested in order to specify that there is no requirement that aplurality of groups be in a specific order. For example, the followingexpression specifies that bends 1 and 2 must be next to each other inthe bend sequence, and bends 3 and 4 must be next to each other in thebend sequence. However, there are no other constraints as to theinclusion and arrangement of other bend operations due to thisconstraint expression.

(*{{1 2}*{3 4}}*).

Some additional example constraint expressions may include ( * 7 ),which means that bend operation 7 must be performed as the last bendoperation in the sequence, and ( * 7 ?), which means that bend operation7 must be performed as the second to last bend operation in thesequence.

The types of operators that can be used to define constraints may beexpanded to include boolean operators such as NOT, OR, and AND. Forexample, a constraint which uses a NOT operator could be ( * NOT 7),which would mean that the seventh bend operation could not be the lastoperation of the sequence.

There is virtually no limit to the types of constraints that can bespecified, and any entity in the planning system, including the variousexperts as well as a human operator of the bend sequence planner, candefine constraints. A constraint manager may be provided, e.g., withinthe bend sequence planner, in order to help maintain the consistency ofconstraints and resolve conflicts that arise between constraints.

By way of example, the types of constraints may include constraints for(1) channels (e.g., as shown in FIG. 26B), (2) angle bends, where thebend line for the flange to be bent intersects and is close to a non-endpoint portion of a bend line of another bend (and both of the bends areto be performed in the same direction, e.g., they are both positivebends) (e.g., as shown in FIG. 27A), and (3) flanges which when bentform a corner with an outside flange and an inside abutting flange(e.g., as shown in FIG. 27C).

The constraint expression for the channel illustrated in FIG. 26Busually must be ( * 2 * 1 * 3 * ), even though a common heuristicprefers that bends on outer bend lines be performed before those ofinner bend lines, which might suggest a constraint of ( * 3 * 2 * 1 * ).This conflict in constraint expressions, if it existed, would have to beresolved in favor of the channel constraint ( * 2 * 1 * 3 * ).

The constraint expression for the pair bends shown in FIG. 27A may be asfollows:

( * 2 * 1 * ).

If the order of bends were different, i.e., if bend 1 was performedbefore bend 2, the flange of bend 2 would not be bendable beyond 90degrees, and thus could not be properly performed (since when bendingmalleable materials with elastic tendencies such as sheet metal, thepart must be bent slightly beyond the goal angle of the bend).

The constraint expression for the pair of bends shown in FIG. 27C may beas follows:

( * 2 * 1 * ).

The importance of complying with this constraint is explained above withrespect to FIG. 25D.

Where appropriate, a human operator of the bend sequence planner (oranother expert/subplanner of the system) may define a constraintexpression which groups all bends on each side of a part together, sothat less time will be spent by switching between sides of the part whenperforming a search for a solution bend sequence. FIG. 27B shows a partwith several bends on each side of the part, where it may be appropriateto group the bends for each side, e.g., by using the followingconstraint expression:

( * { { 1 2 } { 3 4 } {5 6 } } * ).

Since constraints may conflict, a mechanism should be provided forresolving conflicts. As noted above, a constraint manager may beprovided within the bend sequence planner for this purpose. A possibleprioritization scheme could simply discard or ignore constraintexpressions that have a higher assigned priority. The priority assignedto constraint expressions could depend upon what type of constraint itis. For example, human input constraints could be assigned the highestpriority, with machine constraints, part constraints, and optimizationconstraints being assigned respective lower priorities. Accordingly,machine constraints would have the second to highest priority, partconstraints would have the third highest priority and optimizationconstraints would have the fourth highest (i.e., the lowest) priority.

A human input constraint is a constraint input by a human operatorcontrolling the bend sequence planner through a human interface. Amachine constraint is a constraint dictated by limitations of themachines and tooling (e.g., a channel constraint). A part constraint isa constraint dictated by the features of the part (e.g., a constraintdictated by the presence of inside and outside abutting corners).Optimization constraints are constraints that are created in order tospeed up the search for a bend sequence (e.g., a constraint to groupbends together that are on a particular side of the part).

In order to determine if there is a conflict between constraintexpressions, an algorithm may be provided which first checks for thepresence of common operations within a given pair of constraintexpressions. If there is a common operation among the constraintexpressions, they may then be merged together in order to determine ifthey conflict. For example, if (*1*2*) was merged with (*2*3*), theresulting merged constraint expression would be (*1*2*3*). If (*1*2*)was merged with a conflicting expression such as (*2*1*), a null wouldbe the result, thereby indicating that the constraint expressionsconflict with each other.

(a.3) Co-linear (and Compatible) Bends

If two bends have bend lines that are co-linear, e.g., bends 5 and 6 inFIG. 8, and they are compatible (i.e., they have the same bend angles,the same bend radius, and other features which allow the bends to beperformed simultaneously), it is preferred to have the bends performedsimultaneously. For this purpose, heuristics may be provided in order toinfluence the search performed by the bend sequence planner so thatsimultaneous bending of co-linear bends is preferred and thus morelikely to became part of the bend sequence formed by the search. Inaddition, or alternatively, constraints may be specified usingconstraint expressions to require that certain compatible co-linearbends be performed simultaneously if possible (i.e., if the constraintexpression does not conflict with a constraint expression of higherpriority).

(b) The Bend Sequence Planner's State-Space Search Algorithm

In a state-space search algorithm, a solution is obtained by applyingoperators to state-descriptions until an expression describing a goalstate is obtained. In performing a state-space search method, a startnode is associated with an initial state-description, and successors ofthe start node are calculated using operators that are applicable to thestate-description associated with the node. By calculating all of thesuccessors of a node, the node is thereby expanded.

Pointers are set up from each successor node back to its parent node.The pointers may later be used to indicate a solution path back to thestart node, when a goal node is finally found.

The successor nodes are checked to see if they are goal nodes bychecking the associated state-descriptions corresponding to thesuccessor nodes to see if they describe the goal state. It a goal nodehas not yet been found, the process of expanding the nodes, and settingup corresponding pointers, continues when a goal node is found, thepointers are traced back to the start node to produce a solution path.The state-description operators associated with the arcs of the path arethen assembled into a solution sequence.

The above-described steps form a state-space search algorithm.Variations of the above-described algorithm may be defined by the orderin which the nodes are to be expanded. If the nodes are expanded in anorder in which they are generated, the search method is called abreadth-first method. If the most recently generated nodes are expandedfirst, the method is called a depth-first method. Breadth-first anddepth-first methods are blind-search algorithms, since the order inwhich the nodes are expanded is unaffected by the location of the goalnode.

Heuristic information, about the overall nature of the graph and thegeneral direction of the goal, can be utilized to modify the searchprocess. Such information can be used to help direct the search towardthe goal, in an attempt to expand the most promising nodes first. Onetype of heuristic search method is described, e.g., by Nils J. Nilssonin “Problem-Solving Methods in Artificial Intelligence,” notedpreviously.

Blind-search algorithms, such as breadth-first or depth-first, areexhaustive in their approach to find a solution path to a goal node. Inapplication, it is often impractical and time-consuming to use suchmethods, because the search will expand an excessive number of nodesbefore a solution path is found. Such an exhaustive expansion of nodesconsumes more computer memory in order to store the informationassociated with each node, and more time, e.g., to calculate nodeexpansions and points. Accordingly, efficient alternatives toblind-search methods are preferred. Heuristics may be applied to helpfocus the search, based upon special information that is available aboutthe problem being represented by the graph. One way to focus the searchis to reduce the number of successors of each expanded node. Another wayto focus the search is to modify the order in which the nodes areexpanded so that the search can expand outwardly to nodes that appear tobe most promising. Search algorithms which modify the ordering ofnode-expansion are called ordered search algorithms. Ordered searchalgorithms use an evaluation function to rank the nodes that arecandidates for expansion to determine the node which is most likely tobe on the best path to the goal node. In operation of the ordered searchalgorithm an f value is determined at each node n_(f) available forexpansion, where f is an estimate of the cost of a minimal cost pathfrom the start node to the goal node constrained to go through node no.Each succeeding node having the smallest f value is then selected insequence for expansion.

FIG. 20A illustrates a tree produced by an ordered-search algorithmapplied to a blank workpiece that has four sections, which are to bebent upward to form four sides of a box, each side being represented inFIG. 20A by a corresponding number 1, 2, 3, and 4. Each numbered side ofthe box corresponds to a particular bend, including bend 1, bend 2, bend3, and bend 4.

The blank workpiece (stock part) corresponds to start node n₀ which mayalso be called the root node associated with the initialstate-description of the workpiece. The successors of the start node n₀may be calculated by expanding the start node (the root node) to formsuccessor nodes n₁, n₂, n₃, and n₄. At this level of the search, nodesn₁-n₄ correspond respectively to bend 1, bend 2, bend 3, and bend 4.

Node 1 is expanded to include successor nodes n₅, n₆, and n₇ whichcorrespond respectively to bend2, bend3 and bend4, and an additionalsuccessor node n₈ which corresponds to a repositioning (i.e., a repo) ofthe robot gripper's hold on the workpiece. Node 5 is expanded to includesuccessor nodes n₉ and R₁₀ which correspond respectively to bend3 andbend4, and an additional successor node n₁₂, which corresponds to arepo. Node n₈ is expanded to have successor nodes n₁₃ and n₁₄, whichcorrespond respectively to bend4 and a repo. Node n₁₄ is expanded tohave a successor node n₁₄ which is the goal node, because it results inthe final bend for the workpiece.

Bend sequence planner 72 preferably is configured to perform abest-first state space set in order to develop a complete bend sequenceto be performed by the bending workstation. An ordered search algorithmutilizes an evaluation function to rank nodes that are candidates forexpansion to determine the node which is most likely to be on the bestpath to the goal node, i.e., the node which is the best. The first nodecorresponds to the flat part, e.g., as illustrated in FIG. 20A. At eachlevel of the search, the best node which is on an OPEN list will beexpanded, and the expanded node will be taken off OPEN. Depending onwhether or not there are constraints concerning the ordering of certainoperations, all or a portion of the expanded nodes will be placed onOPEN. The expanded nodes which are placed on OPEN will correspond to theremaining bend operations, minus those eliminated due to constraints.

In accordance with a particular embodiment of the present invention,there will be twin nodes corresponding to each bend, including a firsttwin node corresponding to operation of the bend while holding theworkpiece from one side of the workpiece, and a second twin nodecorresponding to performing the same bend, but while holding theworkpiece from the other side of the workpiece. The expanded nodes whichare placed on OPEN may also include one node that represents arepositioning of the robot gripper's grasp on the workpiece (i.e., a“repo”). In accordance with a further feature of the present invention,certain levels of the search may be constrained so that they do notinclude a node for a repo. This is because it would not make sense toperform a repo at one level of the search and again perform a repo atthe very next level. Accordingly, if a repo is performed at an immediateparent node, then bend sequence planner 72 will constrain the placementof a repo node on OPEN.

FIGS. 20A and 20B each illustrate a simple example workpiece 16 havingtwo faces 262, and one bend line 260. In addition, each of FIGS. 20A and20B includes an accompanying diagram of a node expansion from the rootnode n₀ to the first level of a search tree which includes two expandednodes. FIG. 20B shows two expanded nodes, while FIG. 20C shows oneexpanded node and indicates that the other node has been constrained.Referring to FIG. 20B, since only one bend is to be performed onworkpiece 16, only two nodes are shown. The bend may be performed inaccordance with node n₁, whereby bend 1 is performed with face 2 beinginserted into the die space of the bending workstation, or bend 1 may beperformed in accordance with n₂, whereby bend 1 is performed with face 1being inserted into the die space. Referring to FIG. 20C, once workpiece16 is bent along bend line 260, it is apparent that face 1 will resultin a flange having a height which is too small to allow grasping ofworkpiece 16 at that side of the workpiece when performing the bend.Accordingly, in order to perform bend 1 along bend line 260, workpiece16 must be grasped by a robot gripper from the side of workpiece 16corresponding to face 2. In other words, bend 1 must be performed withface 1 being inserted into the die space. Thus, the search treeillustrated in FIG. 20C only includes one node n₁, and shows that whilethe parent node n₀ might normally be expanded to include a second node,the second node has been constrained.

A node may be constrained by eliminating it from consideration as apossible operation within the bend sequence. Such elimination of a nodemay be accomplished by preventing an expansion from including the node,or by simply failing to place the node on the OPEN list.

FIG. 20D illustrates an example workpiece 16 having two co-linear bends,with bend lines 1 and 2. The nodes that may be generated from thisworkpiece include the following: (1,2), (1,1), (2,2), (2,1), ((12),1),and ((12),2). By convention, the holding faces are defined on each sideof the first bend line of the co-linear bend. FIG. 20E illustratesanother example workpiece 16. The holding sides for this co-linear bend(bending at lines 1 and 2 simultaneously) are defined in the followingtwin nodes: ((1 2) 1), ((1 2) 2). Note that the bend twin holding faceis face 1, even though face 1 also extends to the other side of the bendline (i.e., even though it extends to a position which would be behindthe die space during a bend). This is because of the convention notedabove, which is used to choose the bend twin holding face.

FIG. 21 illustrates, in a simplified flow chart, an example embodimentof a state-search algorithm, comprising an ordered search algorithm,based on the algorithm disclosed by Nils J. Nilsson in “Problem-SolvingMethods in Artificial Intelligence”, which may be utilized by the bendsequence planner of the present invention in order to form a bendsequence to be utilized by a bending workstation. After the algorithm isstarted, at step S10, a start node n₀ is placed on a list called OPEN,and a function value f is set equal to 0. Thereafter, in step S12, adetermination is made as to whether there is anything in the OPEN list.If the OPEN list is empty, the process is forwarded to step S14, and anerror indication is given. If the OPEN list is not empty, as determinedat step S12, the process will proceed to step S18.

At step S18, the nodes placed within the OPEN list are checked, and thenode having the smallest f value is removed from OPEN and placed on aCLOSED list. This node is called n_(i). Thereafter, in step S20, adetermination is made as to whether the node n_(f) is a goal node. If itis a goal node, the process is forwarded to step S22, where a solutionpath is generated by tracing back from node n_(f), through its pointerand the pointers of the previous nodes, to the start node n₀. However,if node n_(f) is not the goal node, as determined at step S2O, theprocess will be forwarded to step S24. In step S24, node n_(f) isexpanded to generate all of its successor nodes, called n_(j). If thereare no successors nodes n_(j), the process will return to step S12. Foreach successor node n_(j) that is generated, a computation will be madefor a corresponding f value f(n_(j))=k′(n_(j))+h(n_(j)), where k′ isequal to the sum of the k costs of performing each node from thestarting node to the current node, and h is equal to the projected costfrom the current node to the goal node. Also, in step S24, each of thecomputed f values will be associated with their corresponding successornodes n_(j) that are not already an either the OPEN or CLOSED lists.Such successor nodes n_(j) are then placed an the OPEN list, andpointers are directed from those successor nodes n_(j) back to n_(j).For each successor node n_(j) that was already on an OPEN or CLOSEDlist, an f value is associated with that successor node n_(j) that isequal to the smaller of the f value just computed for that node and thef value already associated with that node. The successor nodes n_(j) onthe CLOSED list who have their associated f values made smaller areplaced on the OPEN list, and the pointers for those successor nodesn_(j) are redirected to n_(f). After execution of step S24, the processwill return to step S12.

(c) Illustrated Example Bend Sequence Planner

FIGS. 22A-22C illustrate a particular example embodiment of a bendsequence planning process to be performed by bend sequence planner 72illustrated in FIG. 5A. The bend sequence planning process is startedupon receipt of a command to commence operation, e.g., as indicated instep S26, by proceeding on receipt of an FEL command to start planning.Once the process starts, and proceeds in step S28, one or more filescorresponding to the parts to be produced are read by the bend sequenceplanner. Such files may be in the form of a shape file includinginformation such as geometric and topological information (a 3D datadescription of the part and a parallel 2D data description of the partcorresponding to the 3D data description), labeled geometric featureswhich are pertinent to determinations to be made by bend sequenceplanner, and a bend graph correlating bends to be performed withgeometric and topological information.

Once the part file has been read in step S28, the process proceeds tosteps S30, S32, and S34, during which each expert is initialized. Moreparticularly, the holding expert, the tooling expert and the motionexpert are each initialized. Once the various experts have beeninitialized, in step S36, a list of bends is built, and calculations areperformed regarding the various features of the parts. For example, acomputation may be performed regarding what the lengths of bends are andwhich bends are co-linear. Thereafter, in step S38, an A* algorithm isinitiated, including steps such as putting a root node n₀ an OPEN list,and setting an f value equal to 0. A determination is then made at stepS40 as to whether the OPEN list is empty. If the list is empty, theprocess will proceed to step S42, and exit with an error indication.Otherwise, if the OPEN list is not empty, the process will proceed tostep S44, in which the node on the OPEN list with the smallest f valuewill be taken and placed on a CLOSED list. The chosen node will becalled n_(i) for, purposes of explaining the steps of the flow charts ofFIG. 22A-FIG. 22D.

In step S46, a determination is made as to whether node n_(f) is a goalnode. If node n_(f) is a goal node, the process proceeds to step S48,where a solution path is generated. Otherwise, if n_(f) is not a goalnode, the process proceeds to step S50 which is shown at the top of FIG.22C.

After generating a solution path in step S48, the process will proceedto step S56 which is shown at the top of FIG. 22D. In step S56, afinalize message is sent along with the bend sequence to each of theexperts, and each of the experts is queried for final detailedinformation which is needed to complete the bend sequence plan.Thereafter, in step S58, the bend sequence planner will await a responsefrom the tooling expert. Once all the final information has beenreceived from the tooling expert, in step S60, the setup of the bendingworkstation will be started. In the meantime, while the setup of theworkstation is being performed, in step S62, the process will await aresponse from the motion expert and the holding expert. Once thecomplete motion expert and holding expert plans have been received, atstep S64, the final plan will be forwarded to the sequencer of thesystem.

Assuming that n, is not determined in step S46 to be the goal node, theprocess will continue at step S50 at the top of FIG. 22C. At this step,node n_(j) will be expanded to obtain its successor nodes n_(j). Thesuccessor nodes will include bend twin nodes for each bend, i.e., twonodes corresponding to each bend, and an additional node for a repo,minus any nodes which are constrained from being successor nodes at thepresent level of the search.

Once the successor nodes have been generated in step S50, a subplanningand cost assignment process is performed in step S52. Thereafter, instep S54, successors n_(j) are each placed on the OPEN list, with thesubplan information and cost information corresponding to each nodebeing associated with each node in the OPEN list (e.g., by usingpointers). The process will then return to step S40 where adetermination will be made as to whether the OPEN list is empty. If theOPEN list is empty, the process will exit with an error indication atstep S42, otherwise the process will proceed to again execute steps S44,S46, S48, S50, S52 and S54.

FIGS. 23A-23D illustrate the subplanning and cost assignment processwhich corresponds to step S52 in the bending sequence planning processillustrated in FIGS. 22A-22D. The subplanning and cost assignmentprocess determines or formulates a subplan and incremental costs whichcorrespond to each of the expanded/successor nodes n_(j) which have notbeen eliminated as a viable node at the present level of the search dueto constraints. For each such expanded/successor node, the processillustrated in FIGS. 23A-23D will be performed. In a first step S66, atest will be performed for the permutability of node n_(j) regarding thesubplan and costs of the holding expert. More particularly, a test willbe performed to determine whether the subplan and costs which will bedetermined by the holding expert will be the same as that alreadydetermined for another “equivalent” node. If such is the case, thesubplan and costs will be identical to that “equivalent” node, and it isunnecessary to again query the holding expert for such information whichwould result in an unneeded use of time. If it is determined at step S68that an equivalent node was found, then the process proceeds to stepS70, where the subplan and costs are copied and associated with thatsuccessor node n_(j). However, if an equivalent node is not found instep S68, the process proceeds to step S72, where the bend sequenceplanner will query the holding expert for a proposed subplan, theincremental k cost, and the incremental h cost. In performing step S72,as soon as a cost of infinity has been evaluated by the holding expert,the present successor node n_(j) will be aborted. Thus, the successornode n_(j) will be discarded it the present level of the search, and thesubplanning and cost assignment process will again start with the nextavailable successor node n_(j).

Once the subplan and costs have been obtained either by step S70 or stepS72, the process will proceed to step S76 (at the top of FIG. 23B),where another test for permutability will be performed regarding thetooling expert subplan and costs. If an equivalent node is found, asdetermined at step S78, the bend sequence planner will copy the subplanand costs corresponding to the equivalent node and associate the samewith the present successor node n_(j). In the alternative, if anequivalent node is not found, the process will proceed to step S82 wherethe tooling expert will be queried for a proposed subplan, a k cost andan h cost. If a cost of infinity is evaluated, the present successornode will be aborted at step S84. Once the proposed subplan and costshave been determined, the process will proceed to step S86, where thebend sequence planner will await the results from the holding expert andthe tooling expert. The process will wait for the results of the holdingexpert and tooling expert queries, since such information is needed bythe motion expert to do its subplanning and cost assignmentcomputations.

In step S88, a test will be performed for the permutability regardingthe motion expert subplan and costs. That is, a test will be performedto determine if the subplan and costs that would be assigned by themotion expert are identical to those which have already been assigned toanother node, the other node thereby being deemed an “equivalent” nodeto the present successor node n_(j) being evaluated. If, at step S90, itis determined that an equivalent node has been found, the process willproceed to step S92, where the subplan and costs of the equivalent nodewill be copied and thereby associated with the present successor noden_(j). However, if an equivalent node is not found, the process willproceed to step S94, where the motion expert will be queried for aproposed subplan, a k cost and an h cost. If any of the costs areinfinity, the present successor node will be aborted, proceeding to anext successor node and again commencing subplanning and cost assignmentfor the next successor node. Assuming that the proposed subplan andcosts have been obtained, the process will proceed to step S98, wherethe results will be awaited from the motion expert. Additionalprocessing may be performed to obtain a subplan and costs regardingdifferent aspects of the system which will be related to performance ofthe overall bend sequence proposed by the bend sequence planner. In thisregard, additional experts may be provided as indicated by the referencenumeral S100. For example, FIG. 5A shows a sensing expert. Thesubplanning and cost assignment process could be appropriately modifiedto include steps such as testing for permutability, querying theadditional expert (e.g., sensing expert) for a proposed subplan andcosts, and, at an appropriate location within the process, awaiting theresults from the additional expert.

Once the results from the motion experts have been obtained, asdetermined at step S98, the process will proceed to step S102 which isshown at the top of FIG. 23D. In step S102 the f value for node n_(j)will be calculated in accordance with the formulaf_(nj)=(k′+h)_(HE)+(k′+h)_(TE)+(k′+h)_(ME). Then, in step S104, the fvalue will be adjusted based upon any heuristics which pertain to thesuccessor node n_(j). In this regard, if it is a desired node, i.e., ithas beneficial or desired heuristics which say that this node ispreferable over other nodes, a value will be added to the f value.However, if the node is undesired, a value will be subtracted from the fvalue.

FIG. 24 illustrates an example flat workpiece 16, and several nodesexpanded during the performance of a state-space search by the bendsequence planner illustrated herein. Various costs are shown which areassigned to the nodes throughout the search process. As shown, flatworkpiece 16 has two portions a, b which are to be bent to form flanges.First flange a is placed in between two tabs c, d. First flange a is tobe bent along bend line 1, and second flange b is to be bent along bendline 2. The first node n₀, i.e., the root node, of the search treecorresponds to flat workpiece 16. Successor nodes of node n₀ includenodes n₁ and n₂, which correspond, respectively, to bend lines 1 and 2.In the illustrated example, it is assumed that a bend along bend line 1would be performed with flange a inserted into the die space of the bendpress, and that a bend along bend line 2 would be performed with flangeb inserted into the die space. Thus, there are no bend twins illustratedin the tree of FIG. 24. There is only one node per bend line.

In the event that the bend sequence planner is designed to assign bendtwin nodes for each bend, the alternate node would likely be constrainedin the present example. For example, it would likely not be possible toperform a bend along bend line 1 by inserting flange b into the bendpress, since flange a is very short, and thus cannot be grasped by arobot gripper during execution of the bend.

At the first level of the search, two successor nodes n₁ and n₂ aregenerated as successor nodes. In forming these two nodes, the bendsequence planner may ask each of the holding expert, tooling expert, andmotion expert or the incremental cost (i.e., h and k costs)corresponding to that node. For example, the costs that are assigned tonode n₁ are illustrated in the box corresponding thereto as shown inFIG. 24. A holding expert assigned a k cost (i.e., the cost that ittakes to move from the parent node n₀ to the present node) of 0. Thissignifies that a grip location can easily be found on workpiece 16, andthat there is need to reposition the grip of the robot on the workpiecebefore performing bend 1 as a first bend in the bend sequence. Theholding expert further assigned an h cost of 30. The number 30represents an approximate amount of time (30 seconds) which it will taketo reposition the gripper's grasp on the workpiece 16 (i.e., to performa repo). This value represents that the holding expert has predictedthat one repo will be needed in order to complete the bend sequenceassociated with workpiece 16. The h cost is a predicted cost to completethe bend sequence from the present node to the final goal node.

The costs assigned by the tooling expert include a k cost of 600 and anh cost of 600. The k cost is the incremental amount of time (due totooling) associated with performing the bend of that node. In this case,in order to perform the bend of bend line 1, a first stage must beplaced on the die rail of the bending workstation. An approximated timefor installing the first stage is 600. Accordingly, the incremental kcost (for tooling) from n₀ to n₁ is 600 seconds. The predictedadditional cost from node n₁ to the goal node (i.e., the h cost fortooling) is calculated to be the time needed to install one additionalstage, and thus is 600 seconds.

The costs assigned by the motion expert include an incremental k cost of5 (an estimated 5 seconds), equal to an approximated robot travel timein moving from n₀ to node n₁. The costs assigned by the motion expertfurther include a predicted future h cost of 15 seconds, which is equalto a running average of all k costs evaluated so far (since n₀)multiplied by a summation of the number of remaining bends and twice thenumber of predicted repos: h=k_(AVE) [number of remaining bends+(numberpredicted repos) (2)]. The number of predicted repos is multiplied by 2,since two movements are required per repositioning. One movement isrequired to take the robot from a present stage to the repo gripper, anda second movement is required to reposition the robot gripper's hold anthe part. The k value for the next node is calculated based upon theamount of time that it takes to move from the repo gripper to theappropriate stage for the next bend.

The alternate node at the first level of the search is node n₂. Thisnode corresponds to bend line 2. The incremental costs include k and hcosts assigned by the holding expert, k and h costs assigned by thetooling expert, and k and h costs assigned by the motion expert. The kand h costs assigned by the holding expert are 0 and 30 respectively.The holding expert assigns a k cost of 0, because no repositioning isnecessary to go from node n₀ to node n₂. However, a holding h cost of 30is assigned because one repo is predicted to be necessary in order tocomplete all of the bends of the bend sequence, i.e., to get to the goalnode. This becomes apparent when viewing workpiece 16. Depending onwhich bend is done first, since the bends are on opposite sides of theworkpiece 16, it will be necessary to reposition the robot's grasp onworkpiece to be at the other side of workpiece 16 in order to performthe other bend. Further, since the workpiece is somewhat narrow, itwould not be possible to locate the robot gripper at either the left orright sides of workpiece 16 so that the workpiece can be grasped at thesame location for both bends. If the robot gripper was positioned at oneof the sides of workpiece 16, robot gripper would likely collide withthe tooling (the punch tool) of the bend press when the die is raised toperform the bend.

The k cost assigned by the tooling expert again is 600, since the bend,being the first bend introduced in the search, will require at least onestage. 600 seconds is an approximated time for installing a stage, andthus is assigned as the incremental k cost to go from node n₀ to noden₂. The h cost assigned by the tooling expert is 600, since a predictedadditional stage will be necessary to go from node n₂ to the goal node.The motion expert assigns a k cost of 4, and an estimated h (future)motion cost of 12. The k cost assigned by the motion expert for node n₂is less than the k cost assigned for node n₁. This is because bend line2 is longer than bend line 1, and thus requires a larger stage. In atypical bending workstation, such as the Amada BM100 workstationillustration in FIG. 1, it is preferred that longer stages be placed inthe center of the die rail, and that shorter stages be placed off to thesides. Thus, to go from an initial position before any bends areperformed (at node n₀) to a center stage would require less movement bythe robot than moving to a stage set off to the side of the die rail.Accordingly, the calculated robot travel time, without regard to thecollisions, from the loader/unloader (L/UL) to the center stage inperforming bend 2 is estimated to be 4 seconds, and less that it wouldtake to get a stage positioned at the left side of the die rail which iswhere the smaller stage would be placed along the die rail. Since the hcost is calculated as a function of the present running average of the kcost calculated so far, the h cost is also a lower value of 12 seconds.

At the first level of the search, the respective total incremental costsperforming bends 1 and 2, respectively, are 1250 and 1246. Accordingly,node n₁ has a total incremental cost of 1250, and node n₂ has a totalincremental cost of 1246, the total cost being assigned by each of theexperts queried by the bend sequence planner.

It is noted that the only two nodes at the first level of the searchincluded a node for performing bend 1, and a node for performing bend 2(nodes n₁ and n₂). The first level did not include a node for performinga repo. This is because the search is constrained so that the first bendto be performed at the first level after the root node does not includea repo. It would be unnecessary for a repo to be performed as a firststep in the bend sequence, since the robot gripper can be placedanywhere at the start to correspond to any particular bend. However, atthe next level of the search, a repo is included as a possible node, inaddition to the one or more bends which comprise the rest of the bendsleading to the goal node. Accordingly, the next level of the searchincludes nodes n₃ which corresponds to bend 1, and n₄ which correspondsto a repo before performing the next bend in the bend sequence. At noden₃, upon being queried by the bend sequence planner, the holding expertassigns a cost of infinity, since there are no available grasp regionsthat were used in performing bend 2 that can also be used to performbend 1. If there was a grasp region that was used in order to performbend 2 that could also be used to perform bend 1, then the robot grippercould be placed within that intersecting region, and the repositioningof the gripper would not be necessary when going from the completed bend2 to bend 1 (i.e., from node n₂ to node n₃). However, in this case, theholding expert has determined that there is no such intersection ofgrasp regions, and thus the incremental k cost for holding is infinity.The predicted h cost is not even relevant, nor are any of the othercosts which might be assigned by the other experts such as the toolingexpert and the motion expert, since bend 1 cannot be performed at thepresent point in the bend sequence, without first performing a repo.Thus, node n₃ is no longer considered, and the bend sequence plannerproceeds to the repo node n₄, and queries the respective experts fortheir assigned costs associated with that node.

After repo node n₄, the holding expert assigns a k cost of 30, whichsignifies that approximately 30 seconds will be needed to perform a repoat the present point in the bend sequence. A predicted h cost of 0 isassigned by the holding expert, since it is predicted that no additionalrepos will be needed between the present node n₄ to the goal node. Afterthe holding expert assigns its cost, the tooling expert, upon beingqueried by the bend sequence planner, assigns a k cost of 600, whichequals the approximate time (600 seconds) to install an additional stagewhich will be needed in order to perform bend 1 (along bend line 1),since the stage which was utilized to perform bend 2 (which has a lengthequal to the length of bend line 2) cannot be used to perform bend 1since such a stage cannot fit between tab portions c and d of workpiece16. No additional predicted stages or tooling change is expected by thetooling expert; and accordingly, the tooling expert assigns an h cost of0 to be associated with node n₄. It is noted that the tooling expert mayinitially determine a total initial h cost based upon the total amountof predicted stages that will be needed to perform the complete bendsequence, either at an initial point in the search before performing thesearch. In the present example, a total initial h cost is calculated tobe 1200, since two predicted stages have been predicted to be necessaryto perform bends 1 and 2 on workpiece 16. Throughout the search, the kcost is either 0 (with no extra stages needed) or 600 (if an additionalstage is needed for the bend corresponding to the present node). The hcost for a given node is equal to the total initial h cost minus all ofthe preceding and current k costs leading up to and including the givennode. Accordingly, for node n₄, since the preceding k cost leading to n₄was 600, and the present k cost for n₄ is 600, the h cost is1200−600−600=0.

The cost assigned by the motion expert to correspond to node n₄ includea k cost of 8 and an h cost of 4. The k cost is estimated to be twicethe average preceding k cost, since two motions are needed in order toperform a repo. One movement is needed to take the workpiece from astage at which the workpiece was left from a previous bend to the repogripper, and the second movement is to move the robot gripper to therepositioned location while the repo gripper is grasping workpiece 16.The predicted h cost assigned by the motion expert for a repo node isthe predicted additional costs needed to perform all future movements inthe bend sequence. In this case, h is estimated to be the h valuecalculated for a previous node n₂ minus the present k cost, and thus isestimated to be 4 seconds for node n₄. The total incremental costs arethen added to the total of all previous k costs preceding that node (inthis case repo node n₄). Thus, all the incremental associated with noden₄ are added to a total previous k costs of 604 which were previouslycalculated in association with node n₂, to obtain a total cost value of1246.

The bend sequence planner will, in performing its state-space search,thus choose n₄ as the best node and will proceed with expanding thatnode to form its successor nodes. The successor nodes of repo node n₄include node n₅. In this case, node n₅ is the goal node, since itresults in the workpiece 16 having all of its bends completed to form a3D part. The costs determined by the relative experts include a presumedholding k cost of 0, a calculated tooling k cost of 600, and acalculated motion k cost of 4. Since the present node n₅ is known to bethe goal node, no h costs are calculated. The previous total k costs 642seconds. Accordingly, 642 is added to the k cost for tooling of 600 andthe k cost for motion of 4 to be equal a total f value of 1246. Such anf value is the cheapest f value among the nodes still left on OPEN.Accordingly, this node will be checked to see if it is a goal node, andif it is a goal node, the solution path will be generated to include (inorder) bend 2 which corresponds to node n₂, a repo which corresponds tonode n₄, and bend 1 which corresponds to node n₅.

(d) Permutability Determination

As described above, in connection with FIGS. 23A-23D, before asking anexpert for the costs associated with a particular node, a test isperformed for the permutability of that node regarding the subplan andcosts for each expert. For example, in step S66 shown at the top of FIG.23A, a test is performed for the permutability of a particular successornode n_(j) to determine if it is merely a permutation of another node,and thus has an equivalent set of subplan and costs. If this is thecase, it would be wasteful to again ask the holding expert for aproposed subplan and associated k and h costs, since these parametersare already known, and can be obtained by merely referring to the otherequivalent nodes. FIG. 28 illustrates a graph of compared histories ofnodes b6′ and b6, which have been generated by the bend sequence plannerin performing its state-space search. Assuming that the subplanning andcost assignment process of the bend sequence planning algorithm wasbeing performed on a particular node b6, at each of steps S66 (FIG.23A), S76 (FIG. 23B), and S88 (FIG. 23C), a test will be performed forthe permutability of that node with any other nodes in the, search treeregarding the holding expert's subplan and costs, the tooling expert'ssubplan and costs and the motion expert's subplan and costs,respectively. In testing whether or not a node is a mere permutation ofanother node within the search tree, a node such as node b6 illustratedin FIG. 28 will be compared to another node in the search tree, such asnode b6′, also illustrated in FIG. 28. In making the comparison, thehistory of node b6, which includes nodes b2, r1, b4, b3, r2, and b5, iscompared to the history of b6′, which includes b2′, r1′, b3′, b4′, r2′and b5′.

Depending on the particular implementation of the bend sequence plannerand the particular calculations made by each of the experts, the methodto be used to determine whether one node is a permutation of anotherwill vary. However, an analysis can be performed of the variouspermutations of nodes, and the various subplans and costs that can beassociated with each node at various levels of the search, in order todetermine under what conditions a node is a mere permutation of anothernode in the search. Based upon the results of the analysis, anappropriate method may be formed for determining whether a node is apermutation of another node, in terms of the subplan and costs assignedfor the node. Thus, while the above-described examples have been givenfor determining the permutability of a node regarding the subplan andcosts assigned by the holding expert and the motion expert,respectively, alternative methods may be used depending upon particularvariations and implementations of the bend sequence planner and theexperts of a system. A similar method can be provided for determiningwhether or not a node is permutable with another node in terms of thesubplan and costs assigned by a motion expert. Thus, a specificembodiment for making that determination is not described in detailherein.

3. Expert Modules, Subplanning, and Dialogue Between Modules

FIGS. 29-31 respectively include charts which depict the dialoguebetween the bend sequence planner and the holding expert, toolingexpert, and motion expert of the illustrated embodiment planning system71 as shown in FIG. 5A. Referring to FIG. 29, which illustrates thedialogue between bend sequence planner 72 and holding expert 82, severalquery arrows Q1, Q2, Q3, Q4 and Q5 are illustrated to represent a querymessage being forwarded from the bend sequence planner 72 to holdingexpert 82. In addition, several response arrows R1, R2, R3, R4, and R5are illustrated to represent response messages from holding expert 82 tobend sequence planner 72. While the queries and responses are indicatedin FIG. 29 with consecutive numbers from 1 to 5, this is not meant toindicate that there could not be additional queries and responses, inbetween, before, or after the queries and responses illustrated in FIG.29. Rather, these numerals are merely provided to facilitate thedescription of the dialogue between the modules as shown in FIG. 29.

At some point before commencing its search (e.g., at step S30 asillustrated in FIG. 22A), bend sequence planner 72 forwards an initialquery Q1 to holding expert 82, which includes, among other things, astart command, and a file name for the part to be produced. This queryQ1 would be forwarded utilizing a VERB “plan . . . ” (which is utilizedto initialize a module for planning a part). Upon receipt of query Q1,the holding expert then performs an input operation indicated by I1,which includes reading an appropriate file which includes geometric,topological, feature information, and other information regarding theparts to be produced. After the part is read, initial planning stepswill be performed, as indicated in block P1. More particularly, holdingexpert 82 will perform gripper selection, which includes picking a robotgripper, and which includes picking a temporary repo gripper. Inaddition, holding expert 82 will predict the minimum nether of reposthat will be needed to complete the overall bend sequence. Afterperformance of the initial planning steps in P1, holding expert 32 thensends the resulting information back to bend sequence planner 72 via aresponse R1. The response includes a savelist which includes a list ofnames of attributes to be saved by bend sequence planner 72. Thesavelist further includes, along with each attribute name, theparameters and values accompanying each attribute to be saved by bendsequence planner 72. The attributes to be saved by bend sequence planner72 at this point include the selected robot gripper, the temporarilyselected repo gripper, and the values indicative of the minimumpredicted number of repos which will be necessary to complete all of thebends of the bend sequence.

After response R1 (e.g., in step S38 of the bend sequence planningprocess illustrated in FIG. 22B), the search is started. Aftercommencing the search, a query Q2 is sent to holding expert 82 (e.g., atstep S72 of the bend sequence planning process illustrated in FIG. 23A).The query Q2 includes bend sequence information, and a request for aproposed subplan, a k cost and an h cast associated with that particularnode. In this regard, a “get” FEL command may be utilized to performthis query. After receipt of query Q2, holding expert 82 will thenperform planning steps indicated in block P2, which include predictingthe number of repos which will be needed after performance of thepresently proposed bend-related operation, determining the grasplocation (i.e., the location at which the robot should grasp a workpiecein order to perform the presently proposed bend), and potential repolocations (for the repo gripper's grasp on the workpiece), and will alsodetermine k and h costs associated with the particular proposedbend-related operation (which would include either a bend or a repo).Once all the planning is performed in block P2, holding expert 82 willthen respond with a response R2 to bend sequence planner 72, theresponse including the k and h costs, a subplan, and various attributeswhich will be saved by bend sequence planner 72 as specified in asavelist forwarded by holding expert to bend sequence planner 72. If thepresently proposed node is not a repo node, k will either be equal to 0or infinity, 0 indicating that no repo is necessary at the present node,and infinity indicating that there are no available places for the robotto grasp the workpiece without first performing a repo. The h value willbe equal to 30 (an estimated amount of time it takes to perform a repo)times the predicted number of repos from the present node to the goalnodes. If the present node is a repo node, k will be equal to 30, if therepo is possible, or infinity if a repo cannot be performed at thepresent level of the search for the present node. The h cost will be 30times the predicted number of repos which will need to be performedafter performance of the present node bend-related operation.

After performance of processing in relation to query Q2 and response R2,bend sequence planner 72 will then query various other experts includingtooling expert 80 and motion expert 84, in order to obtain theirrespective subplans and costs, and repeatedly will, query each of theexperts in association with each node generated during the search inorder to form a complete bend sequence plan which includes nodes fromthe start node to the goal node. Once the search has ended and asolution has been obtained, bend sequence planner 72 will forwardanother query Q3 to holding expert 82 which includes a request for thesuction cup plan, again utilizing the “get” verb of FEL. In response toquery Q3, holding expert 82 will perform suction cup planning asindicated by block P3. Suction cup planning will include a determinationof what locations along the workpiece loader/unloader may place itssuction cups during loading and unloading of the workstation. Once thesuction cup planning has been completed, holding expert 82 will respondwith response R3 to bend sequence planner 72. Bend sequence planner 72will subsequently again query, by query Q4, holding expert 82, for thefinal repo gripper that will be used and the location of the repogripper on the workpiece for various stages of the bend sequence. The“get” verb of FEL may be used for this query. After receipt of query Q4,holding expert 82 will perform the planning indicated in block P4, whichincludes repo planning to be performed after the search. In performingthe repo planning after the search, holding expert 82 chooses a truerepo gripper to be utilized in execution of the resulting bend sequenceplan, and finalizes the repo position based upon the chosen repogripper. After completion of the repo plan after the search, holdingexpert 82 will forward a response R4 to bend sequence planner 72.Thereafter, in query Q5, bend sequence planner 72 will further queryholding expert 82 for a backgage plan. Accordingly, holding expert 82will perform backgage planning as indicated by block P5, and willrespond to bend sequence planner 72 with the appropriate backgage planin response R5.

Once all the planning has been performed by holding expert 82, includingthe final planning after the search, bend sequence planner 72 will havequeried the motion expert 84 for its final plan information, and willawait, before execution of the plan, the results of the final motionplan from motion expert 84. After receipt of the final motion plan frommotion expert 84, bend sequence planner 82 will then proceed to forwardthe final plan to sequencer 76.

In the illustrated dialogue between bend sequence planner 72 and toolingexpert 80 in FIG. 30, several queries are illustrated from bendsequencer planner 72, indicated by query lines Q11, Q12, and Q13, andseveral responses are illustrated by response line R11, R12, and R13. Asindicated by the first query line Q11, at some point in time beforecommencing its search (e.g., at step S32 in the bend sequence planningprocess illustrated in FIG. 22A), bend sequence planner 72 will commandtooling expert 80 to start its processing, and will forward the name ofthe part to be produced with the use of a “plan” verb in FEL. Uponreceipt of query Q1, as indicated by input line I2, tooling expert 80will then read an appropriate part file. Subsequently, tooling expert 80will perform various planning steps as indicated by blocks P11, P12 andP13. These planning steps include selection of a tool profile,bin-packing, and performing a calculation of an initial h value (whichcorresponds to the total number of predicted stages that will be neededto perform all of the bends of the bend sequence). The bin-packingalgorithm comprises the selection of tool segments that will togetheradd up to the appropriate stage length for each stage to be utilized bythe bending workstation in performing the bends of the bend sequence.Once all of the appropriate plan information is gathered in planningblacks P11, P12, and P13, tooling expert 80 will respond as indicated byresponse line R11, to bend sequence planner 72, and will indicate tobend sequence planner 72, via a savelist, various attributes to besaved. Subsequently (e.g., at step S38 in FIG. 22B), the bend sequenceplanner 72 will commence it search. Once the search is commenced, andafter the information has been gathered from holding expert 82, bendsequence planner 72 forwards a query Q12 to tooling expert 80, whichincludes the bend sequence at that point of the search and a query forthe subplan and associated k and h costs. The verb “get” in FEL isutilized for this query. Tooling expert 80 then performs planning steps,as indicated by planning block P14, which include picking of a stagelength to correspond to a bend and a location along that stage where thebend should be performed, arranging the stages, calculating the k and hcosts, and performing fine motion planning. Then, tooling expert 80responds to bend sequence planner 72 via response R12, and forwards thek and h costs and the associated subplan information to bend sequenceplanner 72. A savelist is also included in response R12 which indicatesinformation and attributes that should be saved by the planner.Subsequent queries and responses may be exchanged throughout the search,with tooling expert 80 and with other experts 82 and 84 before thesearch is finished. Once the search ends and a solution has been found(e.g., in step S56 in FIG. 22D of the bend sequence planning process), aquery Q13 instructing the tooling expert to finalize will be forwardedto tooling expert 80. Tooling expert 80 will then perform itsappropriate final processing, and return, via response R13, any finalinformation to bend sequence planner 72. Subsequently, bend sequenceplanner 72 requests final information and final processing to beperformed by motion expert 84 and will await the results thereof. Oncethe final motion planning results have been obtained by motion expert84, bend sequence planner 72 will compile all information to form afinal plan, and will forward the same to sequencer 76.

As illustrated in FIG. 31, bend sequence planner 72 communicates withmotion expert 84 before, during and after performing a search, in theform of queries and responses which may include the queries indicated byquery lines Q21, Q22 and Q23, and respective response lines R21, R22 andR23. Initially (e.g., as indicated at step S34 in FIG. 22A), a firstquery Q21 may be forwarded to motion expert 84 which includes a startcommand, and the name of the part to be produced. Upon receipt of queryQ21, motion expert 84 will then input the appropriate part file and achannel file which represents all of the free space channels throughwhich the part and the robot may be manipulated in performance of thevarious bends and operations of the bend sequence. This input isindicated by I3. Thereafter, motion expert 84 will send a response R21to bend sequence planner 72, indicating, essentially, that theinformation was read in and acknowledging that it is ready for the nextquery by bend sequence planner 72. Sometime thereafter (e.g., at stepS38 in FIG. 22B), the state-space search of the bend sequence planner 72will commence. Then, bend sequence planner 72 will query holding expert82 for various information while performing the first level of thesearch, then query tooling expert 80, and thereafter send a query Q22 tomotion expert 84. Query Q22 includes information about the bendsequence, the gripper location and the bend locations on the stages (inthe form of a bend map). This query may be sent to motion expert 84 byusing a “get” verb in FEL. Upon receipt of query Q22, motion expert 84will perform processing in processing block P21, and thus will develop asubplan and determine the k and h casts for performing the bend proposedby bend sequence planner 72 at that particular point in the bendsequence. The resulting k and h costs and subplan are returned to bendsequence planner in response R22. Afterward, additional processing byother experts 80, 82, and by motion expert 84 may be performed in orderto complete the search.

Once the search has ended and the solution has been obtained, bendsequence planner 72 will send an additional query Q23, which includes afinalize command. With query Q23, bend sequence planner 72 will forwardinformation to motion expert 84 so that motion expert 84 may perform allfinal planning operations. Such forwarded information would include thebend sequence, the gripper locations for each bend in the sequence, therepo locations for each repo to be performed, the bend mapscorresponding to the bends of the bend sequence, and all fine motionplans which have been developed by tooling expert 80, in order to bringthe workpiece into and cut of the die space when performing each bend inthe bend sequence. Motion expert 84 utilizes that information to performthe processing indicated in processing block P22. More particularly,motion expert 84 will figure out the various starting and finishingpoints in order to develop a gross motion plan. A search algorithm isthen performed in order to form paths between the gross motion startingand finishing locations. Then, the resulting gross motion paths arelinked with the fine motion paths so that a complete motion scheme isformed, commencing with acquiring the workpiece from the loader/unloaderduring loading of the workstation, bringing the workpiece to each of itsbends, and finally bringing the finished workpiece to theloader/unloader to be unloaded from the workstation

The complete motion plan is then returned to bend sequence planner 72 ina response R23. Once the complete motion plan has been received by bendsequence planner 72, bend sequence planner 72 may compile the completeplan, and forward the same to sequencer 76 for execution.

FIG. 32 illustrates a flow chart of an example process for performingrobot gripper selection. This process is performed, e.g., in planningblock P1 in FIG. 29. In a first step S128, a library of grippers is readin. Then, in step S130, the process prunes obviously bad grippers, e.g.,if they have certain dimensions which are inappropriate for the type ofwork being performed by the bending workstation. In step S132, a minimumnumber of repos for each gripper is predicted. Thereafter, in step S134,the one or more grippers having the smallest predicted number of reposis selected. Then, in step S136, among the selected grippers, all of thegrippers having the largest width are selected. Among the remaininggrippers, those with the smallest length from the tool center point tothe front tip of the gripper, are selected. Among those selectedgrippers, the grippers with the shortest knuckle height are selected. Ifthere is only one gripper having the largest width among the selectedgrippers, then that gripper will be selected and no furtherdetermination is needed as to the length of the gripper or as to theknuckle height of the gripper. Similarly, if several grippers have thelargest width among the select grippers, but only one gripper has thesmallest length, then that gripper will be selected and no furtherdetermination will be needed as to the knuckle height of the gripper. Ifthere are several grippers left that have an equal shortest knuckleheight, as determined in step S136, then any one of those grippers maybe chosen. Thereafter, in step S138, the chosen gripper is returned tothe holding expert.

As illustrated in FIG. 32, a prediction must be made as to the minimumnumber of repos needed for each gripper in step S132. Such a predictionof the minimum number of repos, before the search, can be performed byutilizing the exemplary process illustrated in FIG. 34A. The goal of theprocess depicted in FIG. 34A is to, for a given robot gripper and agiven part, predict the minimum number of repos that will be needed inorder to form the complete 3D part. Among the information utilized. Inorder to perform the prediction, information is needed regarding boththe 2D part, and 3D part (the completely formed bent part). In a firststep, discrete points are generated around a periphery of a part of a 2Drepresentation of the part. Such discrete points, located a set distancefrom the edge of the part, are illustrated in FIG. 33A. The granularityshown in FIG. 33A is merely for the purpose of explanation of thealgorithm, and does not necessarily reflect a preferred granularity. Thegranularity of the discrete points may be varied in order to obtain anoptimum accuracy, while not sacrificing the speed of the search process.

Assuming a grasp position at a first one of the discrete points, a bendset including all of the possible bends for that robot grasp positionwill be identified in step S142, assuming that the part is still flat,(in 2D) and that the part is at the L/UL. This is repeated for eachdiscrete point around the periphery of the 2D part 16 a (e.g., as shownin FIG. 33A), and all bend sets for each corresponding robot grasp pointare identified.

Thereafter, in step S144, a determination is made as to the minimumnumber of unions of the bend sets determined in step S142 that will forma complete set of bends (i.e., all of the bends of the bend sequence).This minimum number of unions will be identified as a 2D minimum numberof repos R2. Thereafter, in step S146, the discrete points are generatedaround the periphery of a 3D part 16 b (e.g., as shown in FIG. 33B). Itis noted that the granularity shown in FIG. 33B is only shown by way ofexample, and does not necessarily represent the preferred granularityfor performing the present algorithm. The appropriate granularity forthe generation of points around the outer periphery of the part may bemodified in accordance with the desired accuracy and speed of thealgorithm. For each point generated around the periphery of 3D part 16b, the corresponding bend set (i.e., all of the possible bends that maybe performed when the robot is grasping the part at that location) isidentified, thereby identifying all of the bend sets for all of thediscrete points around a periphery of 3D part 16 b. Then, proceeding tostep S150 (in FIG. 34B), the minimum number of unions required to get acomplete set of bends (i.e., all of the bends of the bend sequence) isdetermined, and is called R3 which represents the minimum number of 3Drepos. In performing step S148, all of the possible sets of bends ingrasping at the respective discretized X positions on 3D part 16 b areformed assuming a particular gripper, and further assuming that the 3Dpart is located at the repo station. At step S152, the values R2 and R3are returned to the algorithm for selecting the robot gripper (e.g., asdisclosed in FIG. 32) and to the holding expert. The value R3 representsan upper bound number of predicted repos, since it is more difficult tohold the workpiece when it is completely bent, i.e., a 3D part, than itis to hold the workpiece in performing bends when it is a flat part. Thevalue R2 represents a lower bound number of predicted repos. Theselection of robot gripper algorithm and the holding expert may eachutilize either the lower value R2, the upper value R3, or a combinationof the two in performing their calculations and determinations. Forexample, for purposes of choosing a robot gripper (in step S134 shown inFIG. 32), the lower number R2 may be first considered. If there are morethan one grippers with an equal smallest predicted number of repos R2,but with different values R3, then the grippers with the smallest valueR3 may be selected. These selected grippers, if more than one, wouldthen be further evaluated in accordance with step S136, as shown in theflow chart of FIG. 32.

FIG. 35A illustrates a process for predicting the minimum number ofrepos which can be used during the search. The algorithm for predictingthe minimum number of repos used before the search did not include anevaluation of intermediate parts, in order to save time. In order tohave better accuracy throughout the search, the algorithm depicted inFIG. 35A also considers a farmed intermediate part, and the variationsof the part as it moves throughout the various bends.

In a first step S154, an intermediate part is formed, by calling anappropriate function in a geometric modeling library. The intermediatepart includes all of the bends in the bend sequence so far up to thepresent node of the search. Thereafter, in step S156, discrete pointsare generated around the periphery of the intermediate part, in a mannersimilar to that described in the process of FIGS. 34A-34B, and in amanner similar to that illustrated in FIGS. 33A and 33B. Once thediscrete points are generated, in step S158, a bend set is determinedfor each grasp location point. In other words, a determination is madeas to all of the possible bends that may be performed while the robotgripper is grasping the part at each discretized point. In step S160, adetermination is made as to the minimum number of unions of the bendsets generated in step S158 needed to form a complete set of bends(i.e., all of the bends of the bend sequence). This number is called Ri.Once the value Ri is determined, then, in step S162, discrete points aregenerated around the periphery of the 3D part. A bend set (i.e., thepossible bends that may be performed for each gripper position along thediscretized points) is then identified in step S164. The minimum numberof unions of the bend sets is then determined which would be necessaryto form a complete set of bends (i.e., all of the bends of the bendsequence). That minimum number of unions is referred to as R3. Then, instep S168, a low h cost Ri(c) and a high h cost R3(c) are assigned andreturned to the planner. The cost values Ri(c) and R3(c) are estimatesof the amount of time it takes to perform a repo times the minimumnumber of repos (Ri and R3, respectively). Instead of sending the low hcost and high h cost as noted in step S168 to the holding expert, theprocess for predicting the minimum number of repos during the search maysend the values Ri and R3 themselves.

FIG. 36A illustrates an example process for determining the robot grasplocations, as performed in planning block P2 in the chart depicted inFIG. 29 by holding expert 82. In a first step, S170, an intermediatepart (having the bends corresponding to the present node of thestate-space search of the bend sequence planner) is constructed.Thereafter, in step S172, all edges which are not appropriate forgrasping are rejected. For example, an edge may be rejected if it is nota face which is parallel to the robot's XY plane. In addition, an edgemay be rejected if it is inaccessible by the robot gripper when the partis loaded in the die space. In addition, the edge may be rejected if theedge is too close to the die, so that the robot would collide with thetooling before and/or during the bend operation. The edge may also berejected if grasping the workpiece on such an edge would cause the robotto be outside of its work space.

For each non-rejected edge, the steps following step S172 are performed(shown in FIG. 36A). In step S174, for each non-rejected edge, everyvertex is transformed from sheet coordinates to edge coordinates. Inthis regard, by way of example, an illustration is provided in FIG. 37in order to define an example set of sheet coordinates X_(s) and Y_(s)on a workpiece 16 having bend lines 1, 2, 3, and 4, which may betransformed to edge coordinates X_(e) and Y_(e) which correspond to theedge of workpiece 16 which is next to bend line 1.

In terms of edge coordinates, each, edge is discretized ties into pointsalong the X axis in step S176. Thereafter, in step S178, for eachdiscretized ties point, X_(p), grasp lines are generated which extendalong the Y axis. In order to generate the grasp lines along the Y axis,several process steps are performed. For example, referring to FIG. 38,for a discretized point x_(p), a (broken) grasp line 306 is formed alongthe Y axis. For the discretized ties point x_(p), an initial Y value Ysis proposed which is set at a distance from the edge (e.g., 3 mm). It isassumed that the gripper is oriented to be normal to the X axis in edgecoordinates. A determination is then made as to whether or not the pointYs is out of the robot's work space, while the workpiece is at theloader, the repo station, or at one of the stages. If this is the case,a new point along a line corresponding to the discretized ties point Xpand normal to the edge is found that is within the work space. For thefirst valid Yp, a determination is made as to whether Yp is beyond thegripper's maximum reach. If so, the value Yp is rejected. In addition, adetermination is made as to whether or not the gripper can make good padcontact with the part if the gripper is at the position Yp. If no goodpad contact can be made, the position Yp is rejected. New values for Ypare proposed, until line 306 reaches a first maximum location at whichthe robot can grasp the part, that first maximum position being Yf. Thisdistance is defined by the fact that pads cannot have good contact anymore due to holes or due to a boundary in the part. Far example, amaximum position Yf is found right before a first hole 307 in theworkpiece 16 shown in FIG. 38. The next viable or potential Yp is thenfound along the line running perpendicular to the edge and is defined asa new initial or starting position Ys′. Y values Yp are then proposedand tested until an additional final position Yf′ is found due to limitsbecause the pads cannot have good contact or due to the fact that thepart has a boundary at that location. Thus, as shown in the workpiece inFIG. 38, Yf′ is determined to be just before second hole 308. Thisprocess is repeated until the end of the line 306 reaches the gripper'smaximum reach or the boundary on the opposite side on workpiece 16.Thus, an additional line segment extending from Ys″ to Yf″ is generated.

Once the grasp lines have been generated for each discretized point Xp,later in step S180, a common grasp area is defined for the present bendin the search, and is defined to be the intersection of the currentgrasp lines with the grasp lines determined for previous bends since thelast chosen repo in the search. A k cost of 0 is assigned if theintersection is not equal to 0, and a k cost of infinity is assigned ifthe intersection is 0. This signifies that the present bend cannot beperformed since the grasp areas needed to perform the bend are notcommon with the previous bend. Thereafter, in step S182, a temporarygrasp location is selected within a defined common area.

Whenever it is determined that there is no intersection of graspregions, and thus a repo is necessary, final grasp locations areselected for the bends preceding the repo, since it is known that thegrasp location will not change any further for that set of bends. Afinal grasp location is selected such that a large repo are isgenerated.

FIG. 39 illustrates the evolution of the common grasp area as determinedthroughout a search, as calculated by a determined robotic grasplocations process, e.g., as illustrated in FIGS. 36A-36B. The grasp areafor bend 1 is first determined as illustrated in view A. Then, with bend1 having been already performed, and the corresponding flange being bent(indicated by the cross-hatched lines in view B), the potential graspregions which can be utilized to perform bend 2 are determined asillustrated in view B. The intersection of the regions in views A and Bis then determined as illustrated in view C. Then, bend 2 is performed(indicated by cross-hatched lines in view D), and the total availablegrasp regions which may be utilized to perform bend 3 are determined asshown in view D. To go from bend 2 to bend 3, an intersection is made ofthe regions in views C and D. as shown in view E. This signifies thatthere is no different intersecting region and that a repo must be donebefore bend 3 can be performed (as indicated by the cross-hatched linesin view F). The repo is then performed, and bend 3 is performed. Beforeperforming bend 4, the potential robot grasp regions for that bend aredetermined as illustrated in view F. In order to determine the exactgrasp position to perform bend 4, an intersection is made of the regionsin views D and F, as indicated in view G. This is the region for therobot grasp location that can be utilized in order to perform both bends3 and 4.

Each bend, which has already been performed, is indicated bycross-hatched lines being placed on the flange that is bent. The graspregions are indicated by a solid black line.

FIG. 40 illustrates first and second views of a workpiece 16, the viewsshowing the grasp line regions determined before performing a firstbend, and before performing a second bend, respectively. As can be seenin FIG. 40, the grasp line region 309 comprises a certain large area ofthe workpiece 16. The lower view illustrates the intersection of thegrasp line region (i.e., the grasp area) shown in the top view which canbe utilized to perform the first bend and a grasp line region (notshown) which may be utilized to perform the second bend. Thus, graspline region 310 is a small subset of the grasp line region 309, and maybe utilized as a grasp location to perform both the first bend and thesecond bend.

FIG. 41A illustrates an example embodiment of a process for determiningthe repo gripper locations which will be performed during repo planningafter the search as indicated by planning block P4 in FIG. 29. In afirst step S184, an intermediate part is constructed. The edges whichare not appropriate are then rejected in step S186. For example, theprocess may reject an edge if it does not correspond to a face which isparallel to the robot's X-Y plane. For each non-rejected edge, the stepsfollowing step S186 are performed. In step S188, the intermediate partis transformed from sheet coordinates to edge coordinates. Thereafter,in step S190, the edge of concern is discretized along the X axis (in amanner similar to that illustrated in FIGS. 33A and 33B) with anappropriate granularity. Then, in step S192, grasp lines are generatedalong the Y axis, by generating points along the Y axis from a firstpoint Ys (e.g., 3 mm) to the gripper's maximum reach along the linewhich is placed on the discrete X point. For every point along thatline, if the repo gripper interferes with a previous robot gripperlocation, that Y location is rejected. In addition, for each Y position,if the repo gripper interferes with any portion of the part, that Yposition is rejected. In addition, if there is no good pad contactbetween the repo gripper and the part, that Y position is rejected. Aline is thus drawn as shown in FIG. 38 from an initial position Ys to afinal position Yf which is a first maximum position that the repogripper may grasp the part until it hits a boundary portion (e.g., ahole in the part) Additional sets of initial and final positions Ys andYf are formed until the repo gripper reaches its maximum reach (e.g., atYf″ as shown in FIG. 38), in a manner similar to that performed in theprocess for determining the robot's grasp locations as disclosed inconjunction with FIGS. 36A and 36B.

A final repo location is assigned (in consideration of previous andcurrent robot gripper location) when the search reaches the goal oranother repo becomes necessary.

FIG. 42 illustrates an example embodiment of the process for performingrepo gripper selection before the search. This may not be actuallyimplemented. In a first step S198, a library of grippers is read, and ina second step S200, a conservative repo gripper is selected. Aconservative repo gripper is defined as a gripper which is narrow andshort, and is capable of holding the part (in either 3D or 2D shapes).The selected repo gripper is a temporary solution, since a final repogripper selection will be performed after the search is completed. Therepo gripper selection after the search is illustrated in FIGS. 43A-43B.In a first step S202, all the intermediate part geometries for thevarious bends throughout the bend sequence are constructed. In otherwords, in accordance with the order of bends determined from the search,the appropriate intermediate part geometries corresponding to each bendwithin the bend sequence are constructed. Then, in step S204, grippersare pruned, which are deemed inappropriate due to obvious reasons (e.g.,they cannot grasp a part because of insufficient dimensions). Then, instep S206 available repo grippers are identified based upon two robotgrasp locations which include an initial robot grasp location before therepo and a repositioned robot grasp location. Each of these positionshas been already determined in the search process. If the previouslydetermined temporary repo position, determined during the search, couldbe improved upon in view of the repo grippers that are identified asavailable, then the position is adjusted. In step S208, if there aremore than one available repo grippers (after pruning), then the reposwith the largest width are selected. If there are more than one repogrippers with the largest width, then the ones with the smallest lengthare chosen. If there is more than one repo gripper with the smallestlength, then the one with the shortest knuckle height is chosen. Ifthere are several repo grippers with the same smallest knuckle height,then any one of those is chosen. Currently, a repr gripper is selectedsuch that it allows a larger robot gripper to be selected and itguarantees a successful generation of repo gripper locations. The widthof a repo gripper is determined by the dimension of possible area of 3Dpart for grasping. The knuckle height of a repo gripper is determined tobe taller than the minimum flange height of 3D part.

As shown in FIG. 30, in a planning block P12, a bin-packing algorithm isperformed before the search is started. During the execution of thebin-packing algorithm, a plan is produced that specifies how thesegments should be put together to form each stage in a list of stagesto be chosen from FIG. 44 illustrates an example bin-packing algorithm.In a first step S210, the process builds a list of bend line lengths,and forms a stage length list having stage lengths equal to the lengthsof the bend lines to be formed on the workpiece. In addition, theprocess builds or reads a list of available segment lengths which may bechosen from in order to form the stages in the stage length list. Then,for each different bend line length (i.e., for each stage length) eachof steps S212 and S214 is performed. In step S212, an A* search isperformed in order to determine a combination of segments which could beused to form the particular stage. Then, in step S214, the processreturns a solution set of tool/die segments to the tooling experts.

In performing the A* search, the initial node n₀ is expanded to includea plurality of nodes at the first level of the search, each of theexpanded/successor nodes at the first level corresponding to one of theavailable segment lengths (i.e., lengths of a tool punch andcorresponding die segments). For example, if the available tool segmentlengths are 10 mm, 15 mm, 22 mm, 40 mm, 80 mm and 160 mm, the nodes atthe first level would correspond to each of those segment lengths. The kcost assigned for each successor node is the length of the segmentcorresponding to the present node and the h cost is set equal to thelength of a remaining portion of the stage which is yet to be formed bythe segments (i.e., how far the search process is from the goal).

FIGS. 45-46 illustrate how the h cost that is assigned by the toolingexpert throughout execution of the search, and forwarded to the bendsequence planner 72 (in response R12, as shown in FIG. 30), iscalculated. The tooling h cost is determined as a function of the totalnumber of predicted stages that will be needed to perform all of thebends in the bend sequence.

More specifically, h_(TE) for n_(j), h initial is an initial h costequal to the total number of predicted stages needed to perform allbends of the bend sequence multiplied by an approximate amount of time(e.g., 600 seconds) needed to install each stage, and k′_(TE) for n_(j)is the summed tooling k costs from node n₀ to node n_(j). In order todetermine initial h cost (h_(initial)) (the total predicted number ofstages) a process is performed before the search (in planning black P13in FIG. 30), as shown in FIGS. 45 and 46. A first example workpiece isillustrated in the top portion of FIG. 45, and a second exampleworkpiece is illustrated in the bottom portion of FIG. 45. In the firstexample workpiece, a total of four bends are to be performed, and theworkpiece is to have a total of five faces after the bends areperformed. In the second example workpiece, a total of four bends are tobe performed, and the workpiece will have a total of five faces afterthe bends are performed. In order to assist in the prediction of thetotal amount of stages which will be needed to perform the bends, a bend“test strip” 370 is laid across each bend line of the 2D representationof the workpiece. In each of the examples shown in FIG. 45, such a bend“test strip” 370 is laid across the bend line which is darkened.

FIG. 46 illustrates an example flow chart of the steps that may beperformed in order to determine the initial tooling h-cost(h_(initial)), which is the total number of predicted stages needed toperform all of the bends on the workpiece. In a first step S216, a firststage length which is equal to the length of the longest bend line isplaced within the set of assigned stages. Thereafter, a test isperformed for each bend line, by performing step S218 and the stepsfollowing step S218 for each bend. In step S218, a determination is madeas to whether or not an extra stage is needed. This is done by placing anarrow “test strip” across the bend line in the manner illustrated bythe examples shown in FIG. 45. If a difference value, equal to the totalnumber of faces after placing the test strip over the bend line minusthe total number of faces before the test strip, is less than or equalto 3, then no extra stage is needed. Otherwise, an extra stage isneeded. In a next step S220, if an extra stage is needed (i.e.,predicted), the longest stage (from the stage list) that can be used toperform the bend being tested is assigned, i.e., placed in the set ofassigned stages. Then, a determination is made in step S222 as towhether the newly assigned stage is equal to a stage already in the setof assigned stages. If the newly assigned stage is already in the set ofnewly assigned stages, the newly assigned stage is not appended to theset, as indicated in step S226. However, if it is not already in the setof assigned stages, the newly assigned stage will be appended to theassigned stage set in step S224. Thereafter, the process returns fromeither of steps S224 and S226 to step S218, if there are additional bendlines which need to be evaluated. Once, all the bend lines have beenevaluated by the process, the process proceeds to step S228, where theinitial tooling h_cost is set to the product of 600 and the predictednumber of stages (which is the total number of stages which have beenplaced in the set of assigned stages).

Applying the process steps as shown in FIG. 46 to Example 1 of FIG. 45,the faces after placement of the test strip along the bend line areequal to 8, and the number of faces before the placement of the teststrip along the bend line is equal to 5. Thus, 8−5=3, and no extra stageis predicted. In Example 2 shown in FIG. 45, the number of faces afterthe test strip is placed over the bend line is 10. 10−5=5, which isgreater than 3. Accordingly, an extra stage is predicted for Example 2.

FIG. 47A illustrates a tool selection process overview which forms partof the tool profile selection planning block P11 in FIG. 30. The processbegins at the bend sequence planner in step S471, and proceeds to thetooling expert (tooling module) which operates in step S472. In responseto receipt of a “PLAN” command in FEL from the bend sequence planner,the tooling expert forwards the part's geometric model, bend-graph data,and a tool library to a tool filter module. In step S473, the toolfilter module determines a selected die, die-holder, die-rail and a listof feasible punches. In determining such information, the tool filtermodule performs several steps for each bend to be performed on theworkpiece as indicated by the bend-graph data. The tool filter modulereads necessary data for the bend, and selects the die, die-holder, anddie-rail based upon tonnage, V-width, angle and inside-radiusrequirements. The tool filter module then prunes the list of punches (toform a list of feasible punches) based upon tonnage, tip radius and tipangle constraints.

The process then returns to the tooling module in step S473, which thenforwards the part's geometric model, bend-graph data and a list offeasible punches to a profile select module. Then, in step S474, theprofile select module selects the punch and punch holder to be utilizedby the bending apparatus. In performing the profile selection, for eachbend, the profile select module selects only those punches from thefeasible list whose profile matches the geometry of the part. Puncheswith matching profiles will not collide with the part during the bendingprocess. The profile select module then selects the best punch andpunch-holder accordingly. The appropriate selected punch and punchholder are then returned to the tooling module which continues itsfunctions at step S475.

A more detailed explanation of the algorithm performed by the toolfilter module will now be provided. In a first step, the tool filtermodule reads the following data: the desired inside radius (IR) of eachbend; the part material thickness (T), the part material tensilestrength; the minimum adjacent flange length (the minimum/preferredminimum length (height) of the shorter flange which runs along the bendline of the particular bend of concern); the bend length and bend angle;and a tool library (the tool library includes inverted profiles of thepunches which can be used).

In a second step, for each bend, the tool filter module performs thefollowing steps:

(a) A list of FEASIBLE_DIES is set to empty.

(b) The list of available dies in the library is scanned, and for eachdie:

if its v-width can produce the desired IR within some tolerance, and ifits v-angle closely matches the bend angle, and if the tonnage-per-meterrequired for the v-width and T (computed using a bend force chart andtonnage equations) is within the tonnage capacity of this die,

then, add this die to FEASIBLE_DIES.

It is noted that the tonnage-meter requirement for the v-width and T maybe computed using a force chart and tonnage equations provided by Amadain their press brake tooling catalogues. In addition, or in thealternative, the tonnage-per-meter value may be calculated using thebend chart and tonnage equations provided in the text entitled “NewKnow-how on Sheet-Metal Fabrication Bending Technique,” written by theAmada Sheet Metal Working Research Association, Machinists PublishingCompany, Ltd., First Edition (May 15, 1981), the content of which hasbeen incorporated by reference herein in its entirety.

(c) The die is selected from FEASIBLE_DIES, which most closely satisfiesthe IR, bend angle, the minimum flange, and total tonnage requirements.If the minimum flange length constraint is still not satisfied, then awarning is issued. The appropriate die-holder and die-rail for theselected die are then selected for the selected die.

(d) The list of available punches in the library is then scanned, andfor each punch:

if the tip angle is less than but close to the selected die's v-angle,and if the tip radius is less than and close to the IR, and if thetonnage-per-meter required for this bend is within the tonnage capacityof this punch,

then this punch is added to the list of FEASIBLE_PUNCHES, for this bend.

A more detailed explanation of the steps performed by the profile selectmodule will now be provided.

In an initial step performed by the profile select module, for eachbend, the final (finished) 3D model of the part is aligned in relationto the appropriate tooling in a position in which it would be in thebending press after completion of the bend being evaluated. Then, foreach bend:

(a) The list of FEASIBLE_PUNCHES is scanned for this bend, and for eachpunch, if the 3D geometric model of the punch does not intersect the 3Dgeometric model of the part at the end of this bend, then this punch isa FEASIBLE_PUNCH for this bend. The 3D part model is a sufficientcondition, but may be over constraining and may be modified at a futuredate. For example, intermediate part models, representative of theactual shape of the part at each bend in the sequence could be used asthe profile selection is performed throughout the search process beingperformed by the bend sequence planner.

(b) The punch is selected among the FEASIBLE_PUNCHES, which most closelysatisfies the IR, bend angle, and tonnage requirements. The standard“robot-tooling” punch will be selected if feasible. It is noted that theselected punch may have to be used with its profile inverted (i.e.,inverted in the Y direction/rotated around the Z axis by 180°), in orderto satisfy the intersection test in step (a) above of the profileselection module.

It is noted that one or both of the tool filter module and profileselection module calculations may be performed either before, during orafter the search is performed by the bend sequence planner.

FIGS. 47B-47C illustrate a stage planning process which picks a stageand a location along the stage at which the workpiece will be loadedwhen performing a particular bend in the bend sequence, such planningbeing indicated in block P14 of the dialogue diagram shown in FIG. 30.In a first step S230, an intermediate part model of the part is formed(with the part having the bends up to the present bend in the bendsequence).

In step S232, the biggest non-evaluated stage is chosen from the stagelist (of available stages). Then, in step S234, the present bend in thesearch is simulated with tooling expert (TE) collision checking, withthe part being loaded at onto the tooling stage at a center positionwith respect to the stage. Then, in step S236, a determination is madeas to whether or not there was a collision during simulation of thebend. If there was a collision, the process proceeds to step S238, wherethe bend being evaluated in the search is simulated with TE collisionchecking while the part is loaded at the left side of the tooling stage,with the left end of the bend line being placed just to the left of theleft side of the tooling stage. If a collision is then determined instep S242, the process proceeds to step S246.

If, however, a collision is not determined to have occurred in stepS236, the position at which the workpiece will be loaded onto the stageis set to the center position in step S240, and the process proceeds(via connector B) to step S254 which is shown in FIG. 47C.

If a collision is not determined in step S242, after simulating the bendwith the part positioned on the left side of the stage, the processproceeds from step S242 to S244, where the position for loading theworkpiece on the stage is set to the left position. Then the processproceeds directly to step S254 (via connector B).

In step S246, the bend is simulated with TE collision checking with thepart positioned at the right side of the tooling stage (e.g., as shownin FIG. 48B), with the part being placed on a tooling stage so that theright end of the bend line is placed just to the right of the toolingstage while the bend is performed. If a collision is determined to haveoccurred during this simulation, the process proceeds to step S252. Ifno collision occurred during this simulation as determined in step S248,the process proceeds from step S248 to step S250, wherein the loadingposition is set to the right position, before the process proceeds tostep S254. If a collision did occur as determined at step S248, theprocess proceeds to step S252, wherein the chosen stage (chosen in stepS242) is disregarded, and the process proceeds (via connector C) to stepS232 at the top of FIG. 47B. It is noted that the next non-evaluatedbiggest stage from the stage list will be chosen in step S232 at thispoint. However, the stage planning process may be designed so that itwill go from a “failed” biggest stage straight to a stage having alength approximately equal to the bend line of the particular bend beingevaluated.

In step S254, the evaluated stage is deemed a solution stage.Thereafter, in step S258, the stages are arranged along the die rail,and in step S256, the necessary left-right clearances for stagejuxtapositioning are computed.

The above-referenced tooling expert (TE) collision checking process,referred to in each of steps S234, S238 and S246, may be performed asfollows:

The tooling expert collision checking comprises mainly an intersectiondetermination. The intermediate part corresponding to the particularbend being evaluated in the search is formed, and is further convertedto a B-rep (boundary representation) which is compatible with theNOODLES geometric modeler. Then, an intersection is performed utilizingthe appropriate NOODLES function. First, the number of faces of thepart, as it changes shape throughout performance of the bend, aremonitored. For each of a plurality of discretized shapes of the partthroughout performance of the bend, each of those shapes are intersectedwith the appropriate tools of the bending workstation during theperformance of the bend. The resulting number of faces of the part, foreach shape, is then counter. If the resulting number of faces,intersected with the tools, is greater than the expected nether for thatshape, then there has been a collision.

The above-described steps define a preferred algorithm for performing atooling expert collision checking process. In the alternative, theintermediate part before and after the bend may be modeled by a boundingbox, and the basic solid intersection function provided by NOODLES maybe utilized to determine if the tools intersect with the bonding boxrepresentation of the workpiece for the particular bend being evaluatedduring the search.

A description will now be given of a process for determining thenecessary left-right clearances for juxtapositioning the stages alongthe die rail, as computed in step S256 of the process illustrated inFIGS. 47A-47B. The lateral limits of the part at the particular bendbeing evaluated are calculated based upon the amount by which theworkpiece extends beyond a side edge of the solution tooling stage, anda largest lateral limit for each side of the stage is determined. Thestages arranged adjacent to the present solution stage are thenappropriately spaced to have a gap between the adjacent side edges whichis greater than or equal to the larger of the determined largest laterallimits of the adjacent side edges.

In arranging the stages, in step S258 of the stage planning processshown in FIGS. 47B-47C, the present solution stage (corresponding to thepresently evaluated bend) is placed in the middle of the die rail if itis the longest solution stage that has been evaluated so far in thesearch. On the other hand, if it is the shortest stage that has beendecided upon at the present point in the search, then it is placed atthe first or left position along the die rail. All middle gradations,from the second largest down, are respectively positioned from the thirdposition to the last position along the die rail, the third positionbeing positioned just to the right of the middle position, and the lastposition being the position furthest to the right.

Additional considerations must be taken into account by the bendsequence planner to arrange the layout of the stages when co-linearbends are to be performed simultaneously in performance of the operationsequence. There are issues which must be taken into account, such as theclearance of the part with respect to the stages when the co-linear bendis being performed, and the sizes, arrangement, and number of stagesthat are needed in order to accommodate the co-linear bend while at thesame time best using the resources at hand. One particularly importantresource that must be conserved is the use of space along the die railin order to set up the stages. The number, sizes, and spacings of thestages may be limited because of limitations in die rail space.

When planning the staging for performance of a particular co-linearbend, a decision should be made as to whether the co-linear bend can bedone with only one stage, or whether two spaced stages are needed inorder to allow clearance therebetween. Accordingly, the tool expertshould consider whether the co-linear bends are interrupted (as is thecase in FIG. 20E) or non-interrupted (meaning that one stage can be usedfor both bends, as is the case in FIG. 20D).

A search algorithm could be used, such as A*, in order to come up withan appropriate stage layout that can accommodate co-linear bends, whileminimizing the number of stages and the spacing between stages that areneeded. A significant cost to be taken into account by such a searchalgorithm is the total length of the die rail, the amount of space alongthe die rail a certain staging solution will occupy, and amount of spacealong the die rail remaining at the present level of the bend sequence(being generated by the bend sequence planner).

FIGS. 48A-48C illustrate respective intermediate representations of aworkpiece, being modeled in relation to the tooling during performanceof a bend. In FIG. 48B, the workpiece is at a right position along thestage. In each of FIGS. 48A and 48B, the bend line is shore than thelength of the tooling stage. In FIG. 48C, the workpiece centered alongthe tooling stage, where the bend line is slightly longer than thelength of the tooling stage.

In each of the graphic representations shown in FIGS. 48A-48C, thevarious components of the bend press are modeled, including the toolpunch and the die, along with an intermediate representation of theworkpiece.

FIG. 49 illustrates a fine motion planning process, which may beperformed in planning block P14 of the dialogue chart shown in FIG. 30.In a first step S260 of the process illustrated in FIG. 49, parametersare set and initialization steps are performed. In this regard, the 3Dmodels at the tooling and the part are read, and various initializationfunctions are performed. The goal parameters are set up based upon thetool and part geometry, and the desired clearance. In addition, theportion of the part inside the bend line is rapidly analyzed, and abounding box that surrounds the part is computed.

In step S262, a determination is made as to whether or not a simplesolution path is readily available, by testing if the top of the partcan clear the bottom edge of the tooling punch, and it certain featuresof the part satisfy constraints imposed by the tool geometry and the dieopening. If such a simple solution path is readily available, theprocess proceeds to step S264, where a fine motion plan is quicklygenerated. The process is then forwarded to step S270 where it returnsto the tooling expert with the fine motion plan and the fine motioncost, which is equal to the amount of time that it takes to unload thepart from the bend press.

If a simple solution is not available as determined at step S262, theprocess proceeds to step S266, in which a modified A* set is performed.In performing the search, a plurality of feasible virtual configurationspace nodes are generated and placed on the OPEN list with theirrespective costs. The first level of the search includes severalgenerated intelligent direction feasible VC (virtualconfiguration)-space nodes that were appended to the OPEN list. When anode from the OPEN list is expanded, it is expanded to include severalneighborhood nodes representative of locations in the generalneighborhood of the parent node. Each expanded node is tested forfeasibility by utilizing a geometric intersection test. If the test ispositive (i.e., there is no collision by the use of a negativeintersection function), the expanded node is appended to the OPEN listalong with its cost. The cost is an h cost which is set equal to theEuclidean distance from the expanded node to the goal. The nodes on theOPEN list are continually expanded to lower levels in the search treeuntil the goal is reached or until the OPEN list becomes empty.

At step S268, a determination is made as to whether or not the goal wasreached. If the goal was reached, the fine motion planning processreturns to the tooling expert with the fine motion costs and the finemotion plan in step S270.. If the goal was not reached, the processproceeds to step S272, where the fine motion cost is set to infinity,and is sent to the tooling expert.

FIG. 50 illustrates an example process for determining the motion expertk and h costs, as indicated in planning box P21 of the dialogue chartshown in FIG. 31. In a first step S274, the k cost is calculated to beequal to a calculated robot travel time to take the part from a positionat a stage of an immediate preceding bend to the stage locationcorresponding to the presently evaluated bend in the search, withoutregard to collisions. Then, in step S276, the h cost is calculated to beequal to the product of the running average of the k cost values for theprevious bends and the presently evaluated bend, and the sum of thenumber of remaining bends and twice the number of remaining predictedrepos that will have to be performed before all of the bends in the bendsequence are completed.

In forming the gross motion scheme and the gross motion paths after thesearch is performed, as indicated in planning block P22 of the dialoguechart shown in FIG. 31, a state-space search algorithm, particularly anA* algorithm, may be performed to form each of the steps along the pathfrom one point to another in order to bring the workpiece throughout itsvarious stages in the bend sequence. When generating a path from aninitial start position to a goal position, for a particular operation ofthe bend sequence, before deciding that the path will be the final pathto be used, collision checking may be performed. In order to performthis collision checking, the workpiece, the robot, and the bend pressmay each be modeled, and intersection tests may be performed using theappropriate NOODLES functions. FIG. 51 illustrates a geometric model ofa press brake 304, a workpiece bounding box 300, and a robot 302. Inperforming collision checking in connection with the gross motionplanning, the workpiece is modeled by a bounding box 300. In FIG. 51,the position of the robot 302 and the modeled part 300 is shown in threepositions extending between a stage used for the final bend of the bendsequence to a position at the far right of the diagram which correspondsto a position ready for unloading by the loader/unloader.

4. Geometric Modeling

Each module of planning system 71 utilizes geometric modeling functionsin order to analyze the physical relationships between variouscomponents of the bending workstation and the workpiece as it is beingmoved and developed. Such geometric modeling functions may includerepresenting stock, intermediate, and final past, checking forinterferences during motion planning and assisting in selecting robotgrip positions. In addition, needed geometry information may be providedto assist the sub-planners in determining punch geometry selection, toolplacement, loader/unloader suction cup 31 placement, and interpretationof sensing signals. Simplified geometric representations may be providedfor fast computations (e.g., bounding boxes, convex hulls, and 2Dcross-sections), which may be needed to perform geometric-basedreasoning methods (e.g., oct-tree representations, and configurationspaces). A geometric database of physical components may be providedwhich includes both symbolic descriptions (e.g., labeled features) alongwith actual geometry data of physical components. Other geometricmodeling functions may be provided, although they are not specificallyenumerated herein.

In a particular embodiment of the present invention, NOODLES is utilizedto perform many of the noted modeling functions. Several reasons may begiven for using NOODLES to implement the geometric modeling functions.NOODLES includes a large package of geometric routines and is accessibleto C/C+/C++ source code. In addition, NOODLES is capable of handlingnon-manifold geometry (e.g., 0D, 1D, 2D, 3D, etc.) with the sameroutines, and has a hierarchal structure which can be used to buildgeometry libraries and to store various types of information regardingfeatures of parts.

A modeling mechanism (not shown) may be provided for modeling both upperand lower surfaces (i.e., the thickness) of each sheet metal workpiecethroughout one or more of the design, planning, and execution phases ofthe bending process. It may be useful to have such a complete thicknessrepresentation in the workpiece for certain aspects of the system. Forexample, holding expert 82 may benefit from the added knowledge ofknowing both the upper and lower surfaces of the workpiece, and motionexpert 84 may be able to better plan for and control fine motion of thework piece when it is close to the die and punch tool before and after abending operation.

Referring to FIG. 10, an upper/lower surface modeling mechanism (notshown) performs a thickness transformation between a flat representation114 and a representation with thickness 116, shown at the right of FIG.10. Essentially, the representation with thickness 116 comprises twoflat representations juxtaposed one on the other.

FIG. 11 illustrates an overlapped flange 118 modeled as a flatrepresentation 114 at the left of FIG. 11, and transformed to arepresentation with thickness (i.e., a solid model). Solid model 116 isshown to be equal to an upper surface representation 120 together with alower surface representation 122. Upper surface representation 120 isshown in solid lines, and lower surface representation 122 is shown indotted lines.

FIG. 12 represents an exemplary tree structure which may be utilized tomodel the design representation of a sheet metal workpiece 16. At afirst level, a plurality of shapes 126 are indicated corresponding toworkpiece 16. For each shape 126, several faces 128 are defined, and foreach face, several edges 130 are defined. For each edge, a plurality ofvertices 132 are indicated. For each vertex, a 2D (i.e., stock part)representation 134 may be maintained, along with a 3D (i.e., final part)representation 136 and an intermediate representation 138.

A thickness transformation may be performed, as represented by arrow140, resulting in upper and lower surface representations 142, 144,which each have a tree structure similar to that illustrated above theline in FIG. 12.

FIGS. 17A-17B and 18A-18B illustrate several different types ofgeometric libraries which may be provided in order to aid in theperformance of geometric modeling of the system.

For further information regarding the NOODLES modeling system, andgeometric modeling in general, reference is made to the Reference Manualfor the Noodles Library, by E. Levant Gursoz, EDRC, Carnegie MellonUniversity, Pittsburgh, Pa., and a book by Michael E. Mortenson,entitled Geometric Modeling. The contents of each of these documents areexpressly incorporated herein by reference herein in their entireties.

5. The Query-Based Module Communicating Language (FEL)

In order to formalize the interface between each of the modules of theplanning system, a query-based language called FEL may be used. FEL wasoriginally developed by David Bourne in 1988, and has since been furtherrefined. For more detailed information regarding FEL generally,reference should be made to the several user guides provided by theRobotics Institute at Carnegie Mellon University including: “FeatureExchange Language Programmer's Guide.” David Alan Bourne, Duane T.Williams (Jan. 14, 1994); “Using the Feature Exchange Language in thenext Generation Controller,” David Alan Bourne, Duane T. Williams,CMU-RI-TR-90-19; and “The Operational Feature Exchange Language,” DavidAlan Bourne, Jeff Baird, Paul Erion, and Duane T. Williams,CMU-RI-TR-90-06. The contents of each of these FEL documents are herebyexpressly incorporated by reference herein in their entireties.

FIG. 19 illustrates an exemplary FEL planning message 145 which is beingsent from bend sequence planner 72, as indicated by expression 146, tomotion expert 84, as indicated by expression 148. FEL planning message145 comprises a query command sent from bend sequence planner 72 tomotion expert 84, which provides preliminary information to motionexpert 84 so that it may satisfy the query. An initial parameter settingportion 150 of message 145 is provided immediately after a mainverb/command “get” 152, and includes expressions “type message” 147,“from planning” 146, “to moving” 148, and “state request” 149. Theexpression “type cost” is provided immediately after setting portion150, and signifies that a request is being made for the motion expert totell the planner how much a particular operation will cost. The nextexpression “bends . . . ” 156 queries how expensive it will be toperform bend number 3, after having done bend number 6. The numbers 7and 1 represent a face of the workpiece that will be inserted into thedie space of the bending workstation for bends 6 and 3, respectively.

A next expression “average_cost 2.321” 158 informs the motion expertthat this is the average cost (k-cost) for motion per bend for the bendsthat have previously been done based upon cost values previouslyassigned by the motion expert. In this case, the average cost is 2.321seconds per bend previously performed. A next expression“flange_before_bend” 160 indicates the height (in millimeters) of thetallest flange of concern (indicated in FIG. 18A as 11 millimeters) tobe used by the motion expert to make clearance determinations.Expression “flange_after_bend” 162 similarly indicates the height (inmillimeters) of the tallest flange of concern which will exist after thebend is performed (indicated in FIG. 18 as 17.5 millimeters). A nextexpression “robot_loc” 164 informs the motion expert where the part isby specifying the location of the robot (as it was left upon completionof the previous bend). A last expression in the planning message 145,“bendmap” 166, indicates the respective tool stages for the previousbend and presently proposed bend and where the workpiece should be withrespect to the stage for each bend. The first value 168 represents thatthe location information is give for bend number 6, and a second value170 indicates the stage at which bend number 6 was performed, which inthis case is stage number 1. Several coordinates are listed to the rightof the first and second values 168, 170. The first coordinate value“257.” represents the position of the left edge of the part with respectto the left edge of the stage, and the second coordinate value “−257”represents the position of the left edge of the part with respect to thestage. The value “350.7” represents the position of the right edge ofthe part with respect to the stage. The final value “320.” representsthe position of the stage along the die rail with respect to the leftedge of the die rail.

Generally speaking, the planning message 145 forwards all theinformation which the motion expert will need in order for it togenerate a subplan for moving the workpiece from an initial position(where it is left after performance of a preceding bend) to a positionready for a processed next bend.

A significant feature of the query-based interface structure between theplanner and its various sub-planners (experts) is that when the plannerforwards a query to an expert, it informs the expert of all backgroundinformation that the expert will need to respond to the query. Thus, theexperts need not save information, but can simply respond to the bendsequence planner and return all related information for the bendsequence planner to save.

(a) Configuration of FEL-Based Process Planner

In configuring the process planner 71 illustrated in FIG. 5, each moduleincluding bend sequence planner 72, and experts 80, 82, and 84, is senta command to read its startup configuration file. An example of such acommand could be as follows:

(read ((type file (name “config.s 2.fel”)))

((type message) (from planning) (to tooling) (name “config”)))

After each module has read is startup configuration file, the systemwill be set so that bend sequence planner 72 can use any specifiednumber of experts, e.g., using a command such as the following:

(set ((type experts) (experts (tooling grasping moving))))

After the experts to be used by bend sequence planner 72 are specified,the part design may then be read from CAD system 74 into each module asneeded, and bend sequence planner 72 may start the planning process.

(b) FEL Commands

The following table lists several commands that may be specified by bendsequence planner 72 in participating in a dialogue with the othermodules of the system, including the experts.

FEL MODULE DIALOG COMMANDS SEARCH COMMANDS Finalize collect final planinfo from each module Get get cost information (and other data) for abend Plan initialize a module for planning a part USER COMMANDS Quitcleanup and exit a module Read read files for planning Set set variousmodule options Show show various module data to user

The following table lists several commands that may be specified by bendsequence planner 72 for execution by sequencer 77.

FEL SEQUENCER COMMANDS Print print messages for BM100 operator forMessages setup Programs download programs to NC9R press controller andbackgage controller Startup initialize state of press and robot Getacquire part from various steps of the process Put load part intovarious steps of the process Move move the robot through a series ofpoints Bend initiate bend sequence (backgage and bending)

The “read” command may be used to instruct a module to read certainfiles needed for planning, the files being representative of the designto be produced, and to configure itself in accordance with the design.With use of the “set” command, various module functions may be set,e.g., how to display information, how to interface with other modules,and so on. The “show” user command may be utilized to show variousmodule data to the user, e.g., the various nodes of the A* algorithmwhich represents the various costs or different bends within theproposed bend sequence.

6. Part Design and Modeling

In the illustrated embodiments shown in FIG. 5A, a CAD system 74performs several functions relating to part design and part modeling forplanning system 71. CAD system 74 allows a user to form a design of agiven workpiece by working with simplified, primitive components (ineither 2D or 3D form) on a graphic interface, each primitive componenthaving certain desired dimensions which may be input by the user, inorder to design the workpiece. The user may then utilize a userinterface with CAD system 74 to connect the primitive components and, inaddition, to remove portions, such as holes, slots, etc., from theconnected primitive components. CAD system 74 may then perform featurelabeling functions including labeling several geometric features of theworkpiece, such features having a particular significance in the contextof sheet metal bending. CAD system 74 may also build a bend graph whichassociates various bend-related information with the geometric design ofthe workpiece. CAD system 74 thereby forms an output file which includesgeometric, topological, and bend-related feature information (includinga list of labeled features and a bend graph). All of this information isthen placed into an output shape file which will form the basis ofcommunication with other modules of planning system 71. In this regard,a part modeler may be provided to form an interface between the designsystem's output shape file and the various expert modules 80, 82, and 84(and 85) along with bend sequence planner 72.

A part modeler may be provided which performs various conversions on thedata provided in the output shape file in order to form developed partdata structures which can be used for geometric modeling purposes byeach of the modules of planning system 71. Part modeler may beimplemented in the form of a library which is accessible to each of themodules in planning system 71, which may be utilized to manipulate theinformation in the developed part data structures and/or undevelopeddata structures provided in the output shape file, in order for thevarious modules to utilize the information provided therein to serve anyparticular purpose that they may be addressing at a particular point intime.

FIG. 13A illustrates a functional block diagram of a design system 311which may be provided to perform the functions of CAD system 74 of theillustrated embodiment. Design system 311 performs severaldesign-related functions which may be implemented in the form offunction modules as illustrated in FIG. 13A. Each function module may beimplemented by a particular function provided in a library of functionscomprised by the design system; The functions shown in FIG. 13A includea user interface 312; file I/O 314, view 316, simulation 318, shapedefining 320, hole defining 322, editing 324, and feature labeling 328.Each of these functions may be controlled by a design system controlmodule 326. In order to perform several feature labeling functions, bendgraph module 330 and bend deduction module 332 are each connected tofeature labeling module 328.

Each of the functions are illustrated in FIG. 13A in the form offunction modules. However, it is not necessary that each of thesefunctions be separated into separate modules in the specific manner asillustrated. In the alternative, an overall program or hardware systemmay be provided which allows each of these functions to be performedwithout having any specific interface with other functions of the designsystem. For example, one complete routine may be provided within aprocessor of a computer to implement each and every one of the functionsof the overall design system, without removing several of the generalbenefits provided by the design system disclosed herein.

The file I/O module 314 performs functions such as reading, writing,printing, and performing data exchanges between modules. The viewfunction module 316 performs functions such as zooming in/out, andpanning during display of the part on a graphic interface. The shapemodule 320 is provided to allow a user to specify particular shapes,including rectangular shapes, angles, a Zee, a box, a hat, and so on,which may be put together to form a particular workpiece design. Holemodule 322 is provided for the user to specify various type of cavitiesto be provided in the workpiece, such as cutouts, holes, slots, notchesand so on, to further allow the user to design the workpiece in a mannersimilar to that provided by shape module 320. Edit module 324 isprovided to allow the user to perform various editing functions such asa fillit function, a chamfer function, and changing the workpiecematerial type and/or thickness. Simulation module 318 is provided sothat the user can simulate bending and unfolding of various bends on theworkpiece, thus to get a visual representation of such bends on thegraphic interface to be utilized by the design system.

Feature labeling module 323 is provided to automatically assign featurelabels which pertain to sheet metal bending, and which will thus beuseful to the planning system 71 illustrated herein in forming orgenerating a bend sequence plan with the use of such feature labels.Feature labeling module 328 may generate feature-related informationsuch as corners, setbacks, form features (e.g., dimples, louvers),holes, large radius bend, etc. In addition, feature labeling module 328may be designed so that it directs a bend graph module 330 to form abend graph which includes information organized in a certain way torelate the geographic and topological information to the various bendsto be performed on the 2D workpiece to form the desired 3D finishedworkpiece. In addition, feature labeling module 328 may be designed sothat it directs the performance of bend deduction calculations by a benddeduction module 332. The resulting bend deduction information may thenbe placed within a bend graph listing provided by bend graph module 330.

Various modules provided in the planning system 71 illustrated hereinperform various geometric modeling functions which require that a part(i.e., a workpiece) be modeled. Accordingly, a part modeler should beprovided, and may be provided in the form of a library of functionsaccessible to the various modules in order to interface between thedesign system's output shape files and the various modules withinplanning system 71. FIG. 13B illustrates a part modeling system 333 forperforming this function. Part modeler 333 includes two main functionmodules: a B-REP rearrangement module 336 and an intermediate shapeconversion module 342. The B-REP rearrangement module 336 converts anundeveloped part data structure 334 to either or both of a developed 3Dpart data structure (in B-REP) 338 and a developed 2D part datastructure (in B-REP) 340. Intermediate shape conversion module 342converts the developed 2D part data structure (in B-REP 340) to adeveloped intermediate part data structure (in B-REP) 344.

The undeveloped part data structure 334 (provided by the design system311 as illustrated in FIG. 13A) defines a geometric/topological datastructure that does not take into account bend deduction and that formspart of the output shape file produced by CAD system 74. A developedpart data structure, such as developed 3D part data structure 338 anddeveloped 2D part data structure 340, includes a modified representationof the part that takes into account bend deduction. The noted developedpart data structures are further converted to be in the form of aboundary representation (B-rep) model.

The data structure which resides in the shape output file produced bythe CAD system may be designed to include a shape header which includespart information, followed by a plurality of shapes in a linked list,the linked list ending with a null. In each shape, topological andgeometric information may be provided for both a 3D and a 2Drepresentation of the part. The structure of the shape may include alist of information including the shape type, shape identification, aface list, an edge list, a 3D vertices list, and a 2D vertices list.Each face may have its own structure, which may include a list ofinformation including a face identification, the number of vertices ofthe face, a vertices list for the vertices of the face, and a facenormal vector. For each edge, a structure may be provided which includesinformation such as the edge identification, the edge type, the bentline type, and the vertices index number for that particular edge. Foreach vertex, information may be provided including the verticesidentification, vertices coordinate, 2D coordinates, 3D coordinates andintermediate coordinates. Further information regarding the details ofdata structures and the illustrated CAD system in general are providedin an ME report dated May, 1992 entitled “A Parallel Design System forSheet Metal Parts” presented by Cheng-Hua Wang at the MechanicalEngineering Department, Carnegie Mellon University, Pittsburgh, Pa., thecontents of which are expressly incorporated by reference herein in itsentirety.

As noted above, the CAD system preferably employs a concurrent“Parallel” representation of both the 3D and the 2D versions of the partas it is being designed, and such representations are maintained oncethe part is finally designed for use by planning system 71. In order todemonstrate one of the benefits associated with having such a concurrentand parallel maintenance of 3D and 2D data representations, FIGS. 13Cand 13D are provided. One of the benefits of having a concurrent andparallel design system is that such a system resolves ambiguities whichmay otherwise occur in the design process. For example, a 2D part 346 ais illustrated in FIG. 12C and a 3D part 346 b is shown in FIG. 12D. Byviewing just the 3D representation of 346 b of the part, one may notnotice that inner tab 347 is too long, and cannot possibly be formedfrom a single, malleable piece of sheet metal. This is only clearlyevident by viewing the 2D representation 346 a of the part, whichillustrates the overlap of inner tab 347 as it crosses an inner edgeportion 348 of the part. Accordingly, as can be seen in FIGS. 13C and13D, by having both the 2D and the concurrent 3D representations in agraphic form, the designer can easily resolve ambiguities and recognizeerrors in the design which might otherwise be detected due toambiguities in just viewing one or the other of the 2D and 3Drepresentations during a design. Another benefit associated with such aconcurrent design approach, as noted above, is that it may be easier tomake modifications to one representation (e.g., the 2D representation)instead of the other for a particular type of modification, e.g., addingan inner tab to the part.

FIGS. 14A-14E illustrate a design system graphical user interface 348,with its display changing throughout the process of designing a certaindesired part. Referring, e.g., to FIG. 14A, graphical user interface 348includes a key pad 350, a parameters window 352, a primitive shape 3Dwindow 354, a primitive shape 2D window 356, a model 3D window 358 and amodel 2D window 360. FIG. 14A shows the first introduced primitive shapeprovided an a graphical interface 348 in order to produce the desiredworkpiece as shown in FIG. 14E. The first primitive shape is a box. Theparameters of the box may be specified with the use of key pad 350 andare illustrated in parameters window 352 to have a base which is 100×100(indicated by parameters P[1] and P[2]), and a height equal to 20(indicated by parameter [3]). The 3D version of the primitive shape isillustrated in primitive shape 3D window 354, and the 2D shape of theprimitive shape is illustrated in primitive shape 23 window 356. Sincethis is the first primitive shape being provided for the part design,model 3D window 358 is identical to primitive shape 3D window 354, andmodel 2D window 360 is identical to primitive shape 2D window 356.

FIG. 14B illustrates the next shape to be added which is a rectanglehaving a length of 100 (indicated by parameter [1]), and a width of 15(indicated by parameter [2]). The next primitive shape being added todesign the part is another rectangle having the same parameters as therectangle of FIG. 14B. The next primitive shapes are added to theworkpiece as shown in FIGS. 14C, 14D and 14E.

It is noted that for each primitive shape which is added to theworkpiece, a dotted line is utilized to indicate a bend line. ParameterP[1] corresponds to the X dimension, parameter P[2] corresponds to the Ydimension, and parameter P[3] corresponds to the Z dimension of theprimitive shape being added.

FIGS. 15A-15C are provided to illustrate bend deduction, and the mannerin which it relates to the 3D and 2D dimensions of flanges of aworkpiece. Where a workpiece 362 has a thickness t, and the flanges ofthe workpiece 362 are desired to have lengths a and b, a calculationshould be performed so that the flat 2D representation of the part, whenbent along the appropriate bend line, will indeed form the flangeshaving appropriate dimensions a and b, taking into account the thicknesst of the material, the material type, and the internal radius of thebend line (to the inside surface of the sheet metal). Starting with anundeveloped representation 363 of workpiece 362, the developed 2Drepresentation 364 of workpiece 362 may be calculated by subtracting theappropriate bend deduction (BD) value from the overall dimension a+b.Methods for performing such a calculation are known manner. Accordingly,no specific details are given herein regarding the equation used fordetermining the bend deduction (BD) value.

FIG. 16 illustrates a graphic representation of a bend graph, thegraphic representation being a 2D representation of the workpiecedesigned in the steps illustrated in FIGS. 14A-14E. The bend lines ofthe designed workpiece are labeled as bend lines B1, B2, . . . B8, andeach label comprises a bend line index. Each bend line index is thenassigned a bend sequence number which comprises an initialization value.The bend sequence number indicates the order in the bend sequence inwhich the bend line will be bent, and is assigned for each bend line inaccordance with the plan (i.e., the bend sequence) produced by the bendsequence planner of the illustrated planning system 71. In addition, tothe bend line indices, each bend line is assigned a bend angle. Forexample, in the bend graph illustrated in FIG. 16, an angle of −90.0° isgiven for bend B2, and a bend angle of 90.0° is given for B1. The bendgraph further comprises an indication of the various faces F1-F9 whichare formed on the workpiece once the bends are performed.

Listings are provided in Appendices A and B which respectively include ageometric/topological data structure and a bend graph listing for thepart designed in FIGS. 13A-13E. In addition to the above-noted report tothe Mechanical Engineering Department of Carnegie Mellon University,further reference may be made to an article by Cheng-Hua Wang and RobertH. Sturges, entitled “Concurrent Product/Process Design with MultipleRepresentations of Parts,” IEEE (1993) 1050-4729/93, the content ofwhich is expressly incorporated by reference herein in its entirety.

7. Sequencing and Control

FIG. 52 comprises a block diagram of the various software modules andtheir main interfacing components, such modules including planner 72,sequencer task 76, robot task 92, press and L/UL task 94 and backgagetasks96, speed control task 102, and collision detection task 100.Planner 72 includes interfacing components such as an output queue 72 aand input queue 72 b. The sequencer task 76 includes an input queue 76a, an output queue 76 b, a task response queue 76 c and a sectioncorresponding to several task class member functions 76 d. Output queue72 a of planner 76 is connected to input queue 76 a of sequencer task76. Output queue 76 b of sequencer 76 is connected to input queue 72 bof planner 72.

Robot task 92 includes an input queue 92 a, an output queue 92 b, and aportion corresponding to robot task functions 92 c. Press and L/UL task94 includes an input queue 94 a, an output queue 94 b, and a portioncorresponding to press task functions and L/UL task functions 94 c.Backgage task 96 includes an input queue 96 a, an output queue 96 b, anda portion corresponding to backgage task functions 96 c. Each of inputqueues 92 a, 94 a, and 96 a is connected to input queue 76 a ofsequencer task 76. Each of output queues 92 b, 94 b, and 96 b isconnected to task response queue 76 c of sequencer task 76.

The controller software structure shown in FIG. 52 is representativeonly of an example of the inner connections between planner 72,sequencer task 76, and control system 75, the structure of each of thetasks, and how they are connected. It is within the scope of theinvention disclosed herein to provide variations of a control systemwhich performs the same essential controlling functions, without beingimplemented in the manner illustrated in FIG. 52.

FIG. 53 illustrates an example flow of the process performed bysequencer task 76 illustrated in FIG. 52. Once the sequencer is started,in a first step S280, the sequencer will obtain a new message from theFEL listing at input queue 76 a. In step S282, the sequencer will parsethe FEL sentence, and in step S284, the sequencer will create a dataobject for each task involved. In step S286, the appropriate dataobjects will be placed upon their appropriate task queues (e.g., on oneor more of the input queues of robot task 92, press and L/UL task 94,and backgage task 96). In step S288, the sequencer checks the state ofall tasks involved. Thereafter, in step S290, a determination is made asto whether all the tasks are finished. If not, the sequencer proceeds tostep S292. If all the tasks have finished, the sequencer proceeds fromstep S290 to step S294 where appropriate cleanup operations areperformed (e.g., destroying data objects and resetting flags).

If all the tasks have not finished as determined at step S290, in thenext step S292, a determination is made as to whether or not a time outhas been exceeded. If not, the process returns to step S288. If the timeout has been exceeded, the sequencer proceeds to step S293 whereappropriate error recovery processing is performed. After the cleanupoperations are performed in step S294, a determination is then made instep S296 as to whether the task exit signal has been set. If the taskexit signal has been set, the process will then terminate Otherwise, theprocess will return to step S230 where a new message will be acquiredfrom the FEL input queue.

FIG. 54 is a flow chart of the overall bending process during executionof a single bend. In execution of the bending process, in a first stepS298, the robot places the part into the die space. Thereafter, the partis aligned in the X, Y and rotation directions. This alignment is partof the backgaging operation. In step S300, the press table is raised tothe pinch point, i.e., the point at which the die contacts theworkpiece, which in turn engages with the punch tool so that theworkpiece is in a semi-stable state pinched between the die and toolpunch. In step S302, the bend is executed with bend following (i.e.,with the robot gripper maintaining its hold on the workpiece throughoutthe execution of the bend). Thereafter, in step S304, the press brakewill be opened. Then, in step S306, the part, is unloaded from the diespace. Once the part is unloaded, the bend is completed.

FIG. 55 illustrates the robot task. 92 and the various functions thatmay be provided therein, including general motion functions andsensor-based motion functions. The general motion functions may includea joint space move a cartesian move, and rotation about a point. Thesensor-based motion functions may include a guarded move, bendfollowing, open loop bend, active damping, contact control, andcompliant-part loading. Compliant-part loading comprises loading avibrating compliant-part into the die space of the proper timing so thatthe part fits in the die space and does not collide with theworkstation.

FIG. 56 illustrates the press and L/UL (loader/unloader) task 94, andthe various functions that may be provided within the task. Thefunctions that may be provided for controlling the press may includeraise press, lower press, and bend. The L/UL functions may include aload workpiece, release workpiece, grasp product, and unload product.

FIG. 57 illustrates the backgage task 96, and the various functions thatmay be provided therein. The backgage task may include general motionfunctions and sensor-based motion functions. One general motion functionmay include a move function. The sensor-based motion functions mayinclude a find part edge and a guarded move function

8. Learning for Speed and Quality

The bend system illustrated herein may be provided with one or moremechanisms for learning from the results of the one or more initial runsof a plan, and for modifying the plan accordingly in order to improvethe speed of operations and to also improve the quality of the resultingworkpiece. In this regard, a sensor-based control mechanism may beprovided for performing an operation, including moving a workpiece fromone position to another. The bending apparatus may use a sensor outputto modify the movement of the workpiece, but measure the amount by whichthe movement of the workpiece is modified due to the sensor output.Then, by learning the amount by which the movement of the workpiece wasmodified, the operation may then be controlled, based upon what waslearned, so that the workpiece is moved from one position to anotherwithout modifying the movement of the workpiece utilizing a sensoroutput

FIG. 58 illustrates an example process for performing learningmeasurements and for modifying movement control during multipleexecutions of a generated bend sequence plan, where the movement of theworkpiece from one position to another comprises droop compensation andbackgaging in the X direction. The sensor output comprises a measuredamount of X offset and a measured amount of droop offset of the part.

In a first step of the illustrated process, S308, the part is loaded forbending using droop sensing. The amount of offset of the part, i.e., theamount by which the part is drooping, is sensed and sent back to theplanner (e.g., planner 72 illustrated in FIGS. 5A and 6). Then, in stepS312, the part is side-gaged (gaged in the X direction) to obtain an Xoffset value. The X offset value detected for this bend is sent back tothe planner (or the process manager). Backgaging is then performed toalign the part in the Y direction and also to appropriately rotate thepart so that it is in the appropriate yaw position. In step S318, thebend is then performed.

In step S320, a determination is made as to whether or not there aremore bends to be performed in the present bend sequence being executed.If so, the process returns to step S308, where steps S308-S318 are againperformed to obtain values corresponding to that next bend. If all ofthe bends have been completed, the process proceeds from step S320 tostep S322, at which point the finished part is unloaded, and a newworkpiece is loaded with the loader/unloader. Then in step S324, thepart is loaded for bending using the measured droop offset and measuredX offset values that were previously determined and forwarded to theplanner. By using such values, the bending apparatus can position theworkpiece without performing sensor-based control (or at least with asimplified sensor-based control method) while positioning the workpiece.This should greatly increase the speed with which the workpiece isintroduced into the die space, and reduce Then, in step S326, backgagingis performed to align the part in the Y and rotation (yaw) directions.The bend is then performed in step S328, and a determination is thenmade in step S330 as to whether more bends in the bend sequence stillhave to be performed. If all the bends have been performed, the processproceeds to step S332, at which point a determination is made as towhether more parts are to be made. If more parts are to be made, theprocess returns to step S322.

Due to the repeatability of a typical bending workstation, such as theAmada BM100 bending workstation, the offset values only need to bedetermined by performing one or a few execution runs of the system. Oncethe offset values are determined, the offset values may be used forfuture batch runs of the system, and should be considered dependable formany runs. Accordingly, the process in FIG. 58 is illustrated asreturning from step S332 to step S322 for each new workpiece to beformed, rather than returning all the way back to step S308 forobtaining new offset values.

9. Costing, Scheduling, Part Design and Assembly

The present invention is described as being directed to methods andsubsystems provided in an intelligent design, planning and manufacturingsystem for producing materials such as bent sheet metal parts. Thepresent invention may be further utilized for performing such functionsas costing (i.e., determining how much it will cost to develop certaintypes of parts with a given sheet metal bending work station),scheduling (e.g., determining how much time it will take to perform tomanufacture various parts with a given sheet metal bending work station)and part design and assembly. The planning system 71 of the presentinvention (e.g., as disclosed in FIG. 5A) is capable of generating acomplete sequence of bends and bend-related operations which will beneeded to form a given part. The generated sequence of operations may beaccompanied by a complete plan which specifies all steps needed toexecute the bend sequence in a proper order by the sheet metal bendingwork station. In generating the bend sequence, the planning system 71,through use of experts/subplanners, will determine the consequences ofperforming each bend and other accompanying operations within the bendsequence. Accordingly, without actually executing the resulting plangenerated by planning system 71, planning system 71 will haveinformation as to what the likely amount of time it will take to performall of the necessary operations to manufacture the part with the sheetmetal bending work station. In addition, the planning system 81 will beable to further confirm whether or not the sheet metal bending workstations and available tooling are capable of forming a particulardesigned part. By knowing the consequences of performing the variousoperations in a given plan, planning system 71 can determine theresulting costs, and such information may be utilized to evaluate thecost of producing a given set of parts that form a desired assembly.

In addition, planning system 71 will be able to determine factoryscheduling with its information regarding the time needed to completevarious operations of the plan. In addition, by knowing the limitationsof producing a particular part, the amount of time it would take toproduce the part, and the costs, it will be possible to utilize suchinformation to generate alternative part designs which may result inless cost and less time needed for production of the part.

While planning system 71 has been described specifically as comprising aplurality of experts, with each expert being implement in the form of amodule which is separate from bend sequence planning module 72, planningsystem 71 may be implemented without being separated into modules. Forexample, planning system 71 may be implemented as one overall operationsplanning module. In addition, in the implementation shown in FIG. 5A,the language utilized to communicate between the respective modules maybe a language other than FEL.

The modular structure shown in FIG. 5A, which utilizes a query-basedlanguage, formalizes the interface between the modules, resulting in anopen architecture which can easily be expanded upon by adding furthermodules, and/or by modifying the modules of the planning system. Othermodifications within the general spirit of planning system 71 of theinvention may be made. In order to enhance the speed of operationsperformed by planning system 71, such as the embodiment shown in FIG.5A, each module (i.e., bend sequence planner 72 and subplanners 80, 82,84 and 85) may be implemented on a different computer/processor.

While the invention has been described with reference to severalillustrative embodiments, it is understood that the words which havebeen used herein are words of description, rather than words oflimitation. Changes may be made, within the purview of the appendedclaims, without departing from the scope and the spirit of the inventionin its aspects. Although the invention has been described herein inreference to particular means, materials, and embodiments, it isunderstood that the invention is not to be limited to the particularsdisclosed herein, and that the invention extends to all equivalentstructures, methods, and uses such as are within the scope of theappended claims

What is claimed is:
 1. In a computer having at least one processor and amemory, a device that selects a gripper that holds a workpiece to beutilized by a bending apparatus that bends unfinished workpieces formedof sheets of malleable material, the device comprising: a reader; aformer; a chooser; a predictor; a determiner; and an adjuster; whereinsaid reader reads information describing geometry of a library ofgrippers to be chosen from, said former forms a set of availablegrippers excluding grippers that have certain undesired geometricfeatures, said chooser chooses a gripper from the set of availablegrippers as a function of width of the gripper, length of the gripper,and knuckle height of the gripper, said predictor is adapted to predict,for each gripper within the set of available grippers, a repo numberequal to an estimated number of times the bending apparatus will need tochange the position at which the gripper holds the workpiece in order toperform a complete sequence of bending operations on the workpiece, saiddeterminer is adapted to determine the smallest predicted repo number,and said adjuster is adapted to adjust the set of available grippers toinclude the available grippers having a repo number equal to thesmallest predicted repo number, before choosing a gripper as a functionof the width, length and knuckle height of the gripper.
 2. The deviceaccording to claim 1, wherein the gripper comprises a gripper adapted tohold the workpiece while loading and unloading the workpiece into andfrom a die space of the bending apparatus in order to perform bendingoperations.
 3. The device according to claim 1 the gripper comprising arepo gripper adapted to hold the workpiece while a robot changes a gripposition of the robot on the workpiece.
 4. The device according to claim3, further comprising: an intermediate shape determiner; a constructor;and a utilizer; wherein said intermediate shape determiner is adapted todetermine intermediate shapes of the workpiece, said constructor isadapted to construct data representations of the respective intermediateshapes of the workpiece when repo operations are to be performed by saidbending apparatus, said utilizer is adapted to utilize said intermediateshapes to determine which grippers are excluded from the set ofavailable grippers, and grippers that cannot securely grasp theworkpiece considering all of the constructed intermediate shaperepresentations are adapted to be excluded from the set of availablegrippers.
 5. In a computer having at least one processor and a memory,an apparatus adapted to determine a gripper location, which is alocation on a malleable sheet workpiece at which a gripper is adapted tohold the workpiece while a bending apparatus performs an operation onthe workpiece, the bending apparatus adapted to perform a sequence ofoperations, including said operation on the workpiece in accordance witha bending plan, said sequence of operations comprising a sequence ofbends from a first bend through an Nth bend, the shape of the workpieceadapted to change to at least one intermediate shape as said bendingapparatus progresses through said sequence of bends, said apparatusadapted to determine a gripper location comprising: a former; and adeterminer; wherein said former is adapted to form a set of topographicrepresentations by repeatedly generating, along edges of the workpiece,a graphic representation of areas on the workpiece within which thegripper can be located without hindering performance of a plurality ofoperations in said sequence of operations, taking into consideration theintermediate shapes of the workpiece when each of said plurality ofoperations is performed, and said determiner is adapted to determine theintersection of all the graphic representations within said set tothereby determine the areas common to said plurality of operations insaid sequence of operations.
 6. The apparatus adapted to determine agripper location according to claim 5, wherein said apparatus adapted todetermine a gripper location comprises a changer adapted to change arobot's grip on the workpiece between bends of said sequence of bends.7. The apparatus according to claim 5, wherein said apparatus adapted todetermine a gripper location further comprises a performer adapted toperform a bend within said sequence of bends.
 8. In a computer having atleast one processor and a memory, an apparatus adapted to select toolingto be used in a bending apparatus for bending a workpiece comprising asheet of malleable material, the tooling including at least a die and apunch, the bending apparatus adapted to perform, utilizing the selectedtooling, a sequence of operations comprising a sequence of bends from afirst bend through an Nth bend, said apparatus adapted to determine agripper location comprising: a reader; a former; a chooser; and aproposed subplan generator; wherein said reader is adapted to readinformation describing geometry of a library of dies and punches, saidformer is adapted to form sets of feasible dies and punches excludingdies and punches that have insufficient force capacity to bend theworkpiece and that are incapable of forming bends in the workpieceresulting in desired bend angles and desired inside radii, said chooseris adapted to choose an appropriate die and appropriate punch that mostclosely satisfies force, bend angle, and inside radii requirements byexcluding punches that will likely collide with the workpiece asdetermined by failure of a geometric collision test, and said proposedsubplan generator is adapted to generate a proposed subplan to accompanyeach proposed bend in the sequence of bends, said proposed subplancomprising setup and control information for said bending apparatus. 9.The apparatus adapted to determine a gripper location according to claim8, further comprising a modeler adapted to perform the geometriccollision test by modeling a finished 3-D workpiece; and an aligneradapted to align the modeled finished 3-D workpiece between a model ofeach feasible punch and a model of a chosen die, for each bend in thesequence of bends.
 10. In a computer having at least one processor and amemory, an apparatus for determining a layout of tooling stages along adie rail of a bending apparatus, said bending apparatus adapted to bendworkpieces comprising sheets of malleable material, by performing asequence of operations comprising a sequence of bends from a first bendthrough an Nth, said apparatus adapted to determine a gripper locationcomprising: a decider; a calculator; a determiner; and a spacer; whereinsaid decider is adapted to decide on an arrangement of a plurality oftooling stages along said die rail, said calculator is adapted tocalculate lateral limits based upon the amount by which the workpieceextends beyond a side edge of a tooling stage for the bends of saidsequence of bends, said determiner is adapted to determine a largestlateral limit for each side of each tooling stage, and said spacer isadapted to space adjacently arranged tooling stages to have a gapbetween adjacent side edges that is greater than or equal to the largerof the determined largest lateral limits of adjacent side edges.